the pro-poorness of fertilizer subsidy and its
TRANSCRIPT
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E4
THE PRO-POORNESS OF FERTILIZER SUBSIDY AND ITS IMPLICATIONS ON FOOD
SECURITY IN NIGERIA
ALABI, Reuben Adeolu
Department of Agricultural Economics,
Ambrose Alli University, Ekpoma Edo State, Nigeria
e-mail: [email protected]
and
ADAMS, Oshobugie Ojor
Department of Agricultural Economics,
Ambrose Alli University, Ekpoma Edo State, Nigeria
e-mail: [email protected]
WORK IN PROGRESS(WIP) REPORT SUBMITTED TO AFRICAN
ECONOMIC RESEARCH CONSORTIUM(AERC), NAIROBI, KENYA
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Abstract
We examined the pro-poorness of the newly introduced fertilizer scheme(GES) in Nigeria in
this study. The study made use of the Nigeria General Household Survey (GHS)-Panel Datasets of
2010/2011 and 2012/2013. The data were analysed using pro-poor price indices, average and marginal
benefit incidence analyses to estimate the share of the poor and non-poor in the fertilizer scheme and
to check the pattern of the change in their shares over time in Nigeria. The pro-poorness analysis
suggests that while Voucher Fertilizer Subsidy Scheme seems to be more pro-poor than E-wallet
Fertilizer Scheme on the basis of accessibility, none of them was pro-poor when the analysis was done
on the basis of quantity of fertilizer purchased. On that basis of the share of the poor in Government
expenditure on fertilizer subsidy, the study shows that the share of the rich (N6090 million) and the
richest (N8070million) income group were 3 and 4 times higher than the share of the poorest
quintile(N1979 million) respectively in 2010/2011 in Government expenditure on fertilizer subsidy .
The same trend was noticed in 2012/2013, as the share of the rich (N6813 million) and the richest
(N8735 million) income group were 3 and 4 times higher than the share of the poorest quintile(N2262
million) respectively. The implication of this is that the rich and richest farmers are the immediate
beneficiaries of fertilizer subsidy scheme that are designed to assist poor small-scale farmers in
Nigeria. Apart from income profile, the study shows that education was a distinguishing factor
associated with purchasing fertilizer during fertilizer subsidy scheme in Nigeria. It shows that those
that attended formal schools shared about 70% and 64% of fertilizer subsidy during Fertilizer
Voucher and E-wallet Fertilizer Schemes respectively. The marginal benefit analysis reveals that if
fertilizer subsidy expenditure increased by 100% ( double) the share of the poorest(core poor which is
the target of E-wallet fertilizer subsidy), will decline by about 8%(-0.0791), while the share of the
rich will increase by 8%(0.0803). The study also indicated that the marginal benefit in E-wallet
fertilizer scheme increases with initial accessibility to E-wallet Fertilizer subsidy. The finding
suggests that the poor’s initial rate of access to a fertilizer may determine the relative extent to which
the poor will be benefit from the expansion of the fertilizer subsidy scheme. The conclusion is that
any constraints that limit the accessibility of the poor farmers to fertilizer subsidy will also hinder
their share of the fertilizer subsidy even the government spend more on fertilizer subsidy scheme in
Nigeria. All these findings may cast doubt on the ability of E-wallet Fertilizer Scheme to significantly
increase fertilizer application among farmers in Nigeria. Based on these findings we recommend that
the Federal Government should phase out fertilizer subsidy gradually. After 2016, which is the final
year of E-wallet, fertilizer subsidy be replaced with virile fertilizer market that will sell fertilizer at
cheaper price. This can be made possible by encouraging local production of organic and inorganic
fertilizer by private fertilizer firms. All the fertilizer importing firms should be mandated to open their
fertilizer manufacturing firms between now and next year. Capital constraint is a limiting factor to
accessibility to fertilizer in Nigeria. About N25376 Million and N28270 Million spent on fertilizer
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subsidy in 2010 and 2012 respectively by Nigerian government can be converted to farming input
soft loan scheme for the farmers as the farmers need fertilizer and other inputs to increase their
productivity.
1.0 Introduction
1.1 Background
Nigeria is Sub-Saharan Africa’s most populous country; World Bank report of 2011 put the
population of Nigeria at about 162 million1. It has been observed that Nigeria is one of the poorest
countries in the world despite her rich resource endowment. Research has shown that despite some
positive economic growth experienced in Nigeria, poverty and inequality have worsened(NBS,2012).
The trickle-down effect of growth was not evident in Nigerian case2. Anyanwu (2012) showed that the
poverty level has increased from 28% in 1980 to about 72% in 2011. He revealed further that the
poverty incidence is higher in rural area than urban area in Nigeria. He said that in all the years, rural
poverty incidence had dominated urban poverty. He also indicted that Nigerian poverty depth and
severity are not only high but rising, and that rural poverty was more widespread, deeper, and more
severe than urban poverty3.
The poverty in Nigeria does not only possess a location dimension it is also highly correlated
with occupation in Nigeria. It is hypothesized that occupation has a high correlation with poverty
because occupations which require low amounts of capital, either human or physical, will be
associated with low earnings and therefore with higher poverty rates. This is the case in Nigeria as
67% of the people that are involved in Agriculture were poor, while only 34% of people who are
involved in jobs that require technical profession were poor(NBS,2012). This may be the reason why
Nigeria government directed most of her poverty alleviation programmes and schemes to rural areas
and to agricultural sectors, especially farming.
In order to reduce poverty in rural area and promote food security by developing agriculture,
successive Nigerian government put in place several programmes/initiatives. These
programmes/initiatives include: Fertilizer Subsidy Scheme, Commodity Boards, Agricultural
Research Institutes, National Accelerated Food Production, Nigerian Agricultural Cooperative Banks,
and Agricultural Development Projects (FEWSNET, 2007). Others include: River Basin Development
Authorities, Operation Feed the Nation, Green Revolution, Directorate of Food, Roads and Rural
Infrastructure and National Agricultural Land Development. Furthermore, presidential initiatives on
1 http://data.worldbank.org/indicator/SP.URB.TOTL.IN.ZS 2 Economic growth that is not derived from increases in labour productivity in sectors where the poor work will
not enhance poverty reduction. 3 Some of the reasons advanced for higher poverty in rural area than urban area include the fact that historically
government policy has been biased against rural areas; rural areas are heavily dependent on agricultural
production, which in Nigeria is characterized by low labor productivity and hence low incomes; and natural
disasters such as flooding and drought tend to affect rural areas more heavily than they affect urban areas
(Anyanwu, 2012).
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cocoa, cassava, rice, livestock, fisheries and vegetables and National Special Programme on Food
Security were also implemented. Most of these schemes and programmes have come and gone but the
most persistent of them all is the fertilizer subsidy scheme. The Fertilizer subsidy in Nigeria aims at
making fertilizer price affordable by smallholder farmers in order to increase agricultural productivity
and its efficiency; thereby increase their income and reduce their poverty and food insecurity4.
1.2 Research Issue
According to IDEP (2011), the past Nigerian Government fertilizer subsidy programmes has
been characterized by high level of policy inconsistencies, ambiguities and instabilities that has led to
arguments regarding its basis, application, impacts and sustainability. The gains of the subsidy are
also not widely spread among the targeted beneficiaries (Kabir, 2014), hence the government came on
board with a new pro-poor fertilizer scheme in 2011 that is termed Growth Enhancement Scheme
(GES) for implementation in all the states and Federal Capital Territory (FCT). The rationale for the
Growth Enhancement Support Scheme (GES)5 is through the Voucher Scheme to target beneficiaries
through the electronic system(E-wallet), by encouraging the delivery of GES, via the development of
private sector distribution channels.
According to the Federal Ministry of Agriculture and Rural Development (FMARD), Growth
Enhancement Support Scheme (GES) represents a policy and pragmatic shift within the existing
Fertilizer Market Stabilization Programme and it puts the resource constrained farmer at its center
through the provision of series of incentives to encourage the critical actors in the fertilizer value
chain to work together to improve productivity, household food security and income of the farmer. It
is a special scheme introduced by the Federal Government under President Jonathan’s Agricultural
Transformation Agenda (ATA), which seeks to increase farmers’ access to subsidized farm inputs
such as fertilisers and improved seeds through the private sector.
The Goals of GES are:
Target 5 million farmers in each year for 4 years that will receive GES in their mobile phone
directly totaling 20 million at the end of 4 years.
To increase productivity of farmers across the length and breadth of the country through
increased use of fertilizer to 50kg/ha from current 13kg/ha6.
4 According to World Bank (2014), the achievement of self-sufficiency in basic food supply and the attainment
of food security is main policy agricultural objective in Nigeria. The main features of the policy include the
evolution of strategies that will bring about improvement in the level of technical and economic efficiency in
food and tree crops production. 5 FMARD (2012). Growth Enhancement Scheme. Available on the internet at http://www.fmard.gov.ng/index.p
hp/ges/86-ges-overview 6 The Africa Fertilizer Summit was convened by the African Union’s New Partnership for Africa’s
Development (NEPAD) and implemented by IFDC. According to the Summit the average fertilizer used in
Africa should be increased to 50kg/ha.
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Change the role of Government from direct procurement and distribution of fertilizer to a
facilitator of procurement, regulator of fertilizer quality and catalyst of active private sector
participation in the fertilizer value chain
The FMARD (2014) claimed that no fewer than 10 million farmers have now been captured in the
database of the Growth Enhancement Support (GES) currently being implemented by the FMARD7 in
conjunction with private sector firms. According to information provided by Cellulant Nigeria, the
technology partner of the scheme, an increasing number of farmers have been captured in recent
months following the success of the scheme in 2012. There is therefore the need for study to
empirically investigate this innovative and new scheme in order to improve it so that it will not end
up as other past agricultural schemes in Nigeria. We need to know if this new fertilizer scheme has
benefited the poor farmers more than the non-poor farmers. Does literate farmers, urban farmer and
male farmers benefited more proportionately than illiterate farmer, rural farmer and female farmer
respectively? Has the scheme led to increase in the use of fertilizer in Nigeria? Has the new scheme
increased the productivity of the participating farmers? If the scheme is expanded will the poor
farmers benefited more than non-poor farmers? The empirical answers to some of these questions
will help in effectiveness and efficiency of the GES in Nigeria and make it pro-poor.
1.3 Objectives of the Study
The broad objective of this study is to analyse the pro-poorness of the new fertilizer subsidy scheme
(GES) and establish its implication on food security in Nigeria. Specifically, we shall:
(1) Review the GES Scheme since its inception in Nigeria.
(2) Estimate the pro-poor indices for GES among the farmers in Nigeria.
(3) Compute the average and marginal benefit incidence of GES based on location, gender,
literacy and regions in Nigeria.
(4) Compare the yield of the GES participating farmers before (2010/2011) and during the
scheme (2012/2013).
2.0 Review of Literature and Conceptual Framework
2.1 Review of Fertilizer Production, Consumption, Importation, Distribution and Finance in
Nigeria
The fertilizer market of Nigeria was originally driven by government policies of direct
participation in production, procurement and distribution. For many years, all fertilizer used in
country was imported by the Federal Government of Nigeria (FGN) and state governments. By the
early 1970s, the FGN established the Fertilizer Procurement and Distribution Division (FPDD) with
its supporting institutions under the Federal Ministry of Agriculture (but now called Federal Ministry
of Agriculture and Rural Development) to facilitate the formulation and coordination of all fertilizer
policies at the national level and to centralize procurement and distribution. By the mid-1970s, the
7 http://www.fmard.gov.ng/news_inside.php?nid=135
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FGN started to implement domestic production of fertilizer under the FPDD, making large
investments for the establishment of production and blending plants. This initiative was supported by
the private sector with the purpose of meeting the country fertilizer needs. Under this initiative, two
major fertilizer plants were established: the Federal Superphosphate Fertilizer Company (FSFC) and
the National Fertilizer Company of Nigeria (NAFCON) for the production of urea. The FSFC was
established in 1973 with an installed production capacity of 100,000 metric tonnes of single
superphosphate (SSP) fertilizer, mainly to supply the national market with the phosphate rock from
Kaduna State. Since its establishment, FSFC never utilized its full potential; hence the plant was shut
down in 2000. The plant resumed production of TSP in 2008 after being privatized and acquired by
TAK Continental (IFDC/PROMIDIA, 2008). The second established plant, for the production of
ammonia and urea, was NAFCON in 1981 near Port Harcourt. The plant entered into full operation by
the mid-1980s and was recognized as the only production facility in West Africa for granulated
nitrogen products. This plant has an installed production capacity of 1,000 mt of ammonia, about
1,500 mt of urea, in addition to the 1,650-mt blending capacity of NPK per day. The NAFCON plant
stopped operating in 1997 as a result of poor management and damaged equipment
(IFDC/PROMIDIA, 2008). More recently, NAFCON was privatized, acquired by Notore Chemical
Industries Ltd. Notore’s plans were to reactivate the plant with a gradual increase in production
starting with urea and NPK blends for domestic use and export, then scale up production until it
reaches maximum capacity. However, these plans were delayed due to technical problems with the
operation of the plant8.
After NAFCON stopped operations in 1997, the urea supply dried out, forcing these plants
to operate mostly with imported products (N, P and K). Most of these plants have been out of
operation for many years and the equipment has become deteriorated and obsolete. As a result, their
respective administrative structures prefer to keep the fertilizer operations by competing in the
government tenders for supplying imported fertilizers to the market under the subsidy program9.
The fertilizer market in Nigeria is the largest in West Africa representing an average of 45
percent of total fertilizer consumption (in nutrients base) in the Economic Community of West
African States (ECOWAS), followed by Burkina Faso, Côte d’Ivoire, Ghana and Mali for the years
2005-2009 (Fuentes et al, 2012). Yet, the average nutrient fertilizer consumption was estimated at
around 2.0 kg/ha in 2009 (FAOSTAT, 2011), which is below the ECOWAS’s average of 4.0 kg/ha.
8 In addition to FSFC and NAFCON, a handful of bulk-blending plants with varying production/ processing
capacities were established across the country in different states. Ownership of these blending plants ranged
from state governments to private ownership or mixed capital investments. Out of more than 30 established
blending plants, only a few reached active production after installation (The NEEDS, 2004). Even at the peak of
production, the combined output of all plants operating in Nigeria was less than 1 million metric tonnes of
products, accounting for about one-third of the country’s installed capacity. 9 Importing N, P and K for blending would require investment in repairs and updating equipment. Efforts were
being made to reopen some of the plants with the intention to seek efficiency in the supply of blended fertilizer
by blending locally and, in the process, reduce cost and the price for farmers (FMARD, 2008).
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Nigeria imports the bulk of its fertilizer and, like most countries in the region it is a price taker in the
international market. Thus, the increased price fluctuation in the international market may explain in
part the high price farmers pay for fertilizer in the Nigerian market. Additionally, there is ample
evidence suggesting that in Nigeria, there are market constraints throughout the domestic supply chain
that contribute to about 42 percent of the total fertilizer domestic cost, almost doubling the price
farmers ultimately pay relative to the international/border price (Fuentes et al, 2012).
The main types of fertilizer imported and distributed in Nigeria include straight products,
particularly urea and phosphate compound fertilizer and, more commonly, various NPK compounds
and blended formulations (i.e., triple 15, 20-10-10, etc.), according to the specific crop needs.
According to Fuentes et al (2012), during 1990-2009 period, the average quantity of fertilizer
imported and consumed in Nigeria was about 252,000 nutrients metric tons per year which ranges
between 69,000 metric tons per year in 2004 and about 498,000 metric tons per year in 2008.
Fertilizer imports declined sharply between 1993 and 1997 following the disengagement of the FGN
from fertilizer production and importation, as a result of market liberalization policy and the
elimination of subsidies. This disengagement caused problems with the supply of fertilizer since the
private sector was not able to take over the responsibility of imports and distribution. Consequently,
during the 1997/98 farming season, the fertilizer market suffered shortages resulting in low
agricultural production. These low fertilizer imports and consumption levels lasted until 1999, when
consumption started increasing again. After a period of continuous private sector investments to fill
the void left by the government, the FGN reintroduced subsidies in late 1990s at a 25-percent level
and resumed production and importation. Since then, there has been a slow and oscillated upward
trend in fertilizer importation and use in Nigeria, attributed to the effect of the FGN stabilization
policy on farmers’ fertilizer demands. This policy had the unexpected effect of constraining farmers’
specific demands to relatively small quantities, according to the amounts of fertilizer subsidized and
supplied by the government. This is in opposition to relying on the capacity of the private sector to
supply larger quantities, according to farmers’ actual needs. This erratic pattern reflects the
inconsistency of the government policy on fertilizer imports, which has sent mixed signals to the
private sector on whether to supply larger amounts of fertilizer from one year to the other (Fuentes et
al, 2012). Prior to 2007, the FGN awarded contracts to suppliers who had limited capacity to
undertake the entire importation process10.
10 Most of these actors represented private entrepreneurs registered specifically to support the government in
fertilizer importation under the subsidy program. However, many of them did not import fertilizer but
were engaged in arbitrage, using the contracts issued by the government as negotiable instruments with the few
established companies with the capability and the logistics to actually import the products. This practice
contributed to higher prices of imported fertilizers under the government contracts because of successive
markups introduced in the process. This practice is one of the reasons the government has been encouraged to
withdraw from importation and distribution of fertilizer.
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After 2008 the FGN reduced the number of eligible contractors to three – TAK Continental11,
Golden Fertilizers12 and Notore Chemicals13. This practice may prevent other genuine participants
from competing in the Nigerian fertilizer market because of the difficulty competing against heavily
subsidized products. Many of these have now stopped importing and those that remain do not have
access to FGN contracts and have developed strong affiliations with the state governments to supply
the product.
In Nigeria, three fertilizer distribution networks have been operating since the country’s
independence. At first the government created a network of ‘Primary Distribution Points’ (PDPs) at
different locations in the country operated by the FPDD. Under this arrangement, the subsidy on
fertilizer was for transportation. The FPDD hired trucks from the private sector to move products
from Lagos port to the PDPs for distribution to all states of the federation. The products were
deposited at the Farm Service Centers (FSC) scattered all over the states, where fertilizer was sold to
farmers. This practice ceased to operate after 1997 when the government temporarily withdrew from
fertilizer distribution. Subsequently, many other options were employed, including the engagement of
NAFCON by the government as the sole distributor of domestic and imported products to different
parts of the country. Prior to 2011, there exists a dual fertilizer distribution system in Nigeria.
This consists of two distribution channels: the public and the private distribution channels, dominated
by the public channel. The public channel arrangement involves the private sector in the acquisition
of fertilizer from the international market (imports) through a tender process. Private
importers/suppliers incorporate distribution costs in their bids, according to procurement contracts to
deliver the product to designated state warehouses. The product is then distributed through public
channels without the participation of the private sector distribution network. Additional imported
quantities by private importers are distributed through the small-scale agro-input dealers located in the
local markets and semi-urban areas. The public distribution system of subsidized fertilizer is
embedded in inefficiencies and endemic mismanagement practices. The international procurement of
subsidized fertilizer for the federal and state governments is done through the private sector.
Nevertheless, there had been limited incentive and opportunities for the private sector to
develop alternate private distribution channels down to the final user and beneficiaries of the subsidy
11 TAK Continental, a family own company, is the largest fertilizer supplier to the Nigerian market. The
company owns five blending plants in several states of Nigeria and the Federal Superphosphate manufacturing
plant in Kaduna state. 12 Golden Fertilizers is a Greek-owned company, whose main operation in Nigeria is flour milling. The
company has a subsidiary shipping line (Gold Star Shipping) and a trading business, which allows them to bring
in mixed cargoes of wheat and fertilizer into the Nigerian market. 13 Notore Chemicals PLC is a consortium formed by Nigerian and African investors (60 percent) in addition to
an Egyptian fertilizer manufacturer and U.S. investors (20 percent, respectively). NAFCON the only domestic
compound (ammonia and urea) fertilizer product manufacturer plant in Nigeria was commissioned to Notore
Chemicals PLC for its operation in 2008 by the FGN, after being closed for 10 years.
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and fertilizer. The main reason, according to distributors, is the difficulty to make a reasonable profit
and expand supply and distribution nearer to the farmers (Fuentes et al, 2012).
Each year, the FGN allocates funds for the provision of fertilizer. The FGN, through the FFD,
consolidates orders from and allocates volumes depending on the federal budget allocation to each of
the states. Under the agricultural market stabilization program, the FGN pays a 25-percent subsidy at
the source (importers or producers) and charges the remaining 75 percent of the cost to the states. The
intent with this program has been to establish a revolving fertilizer fund. Therefore, the states are to
remit funds equivalent to 75 percent of fertilizer cost (after subsidy) to the FGN from fertilizer sales
(Fuentes et al, 2012)14. Under the agricultural market stabilization subsidy program, the FGN starts
negotiations with the states and suppliers between September and November of the preceding year,
negotiations that may last until January of the following year. During these negotiations, prices and
quantities supplied are determined for each importer based on tenders. The negotiated price is based
on free on board (f.o.b.) market prices during or at the time of negotiation. Consequently, the price is
fixed at that point for the following cropping seasons. A single price for all of Nigeria is determined
for each product, meaning that the freight cost of delivery must be standardized to all nominated state
government storage sites in each state. All products have to be supplied before the end of October of
the year of the contract. Allocations of procurement contracts cannot be made until the federal budget
is approved, which typically occurs early in the new year after the fertilizer budget was approved. As
a consequence, Nigerian farmers normally do not receive an adequate supply of fertilizer in time for
the cropping season (Fuentes et al, 2012). At that time, there is limited product in the country,
because suppliers are not prepared to take the risk of importing products without government
contracts. The fertilizer season starts in the south in May and continues until July in the northern
regions. Fertilizer products to be delivered are typically assigned to a state representative who is in
charge of receiving the product at the warehouses15.
2.2 Review of Fertilizer Policies in Nigeria
Agricultural policy in Nigeria has developed considerably since the country’s independence.
In1998, after years of neglect, the government adopted an agricultural policy that had the objective,
14 However, in reality, these remittances rarely happen and that is why the FGN deducts the outstanding funds
from the Federal Government Federation Account payments to the states from the division of oil revenues. State
and local government authorities (LGAs) can add to the amount of subsidized fertilizer supplied by the FGN
through direct purchase from importers and/or add additional subsidy. This can amount to as much as 50 percent
additional subsidy for a maximum of 75 percent combined FGN, state and LGA subsidies. Under the FGN
subsidy program, once the product is delivered to the states, the amount of fertilizer to be distributed to
beneficiary farmers is determined by allocation committees at the state and local levels, where the state
committee is appointed by the state governor. The states may then choose whether to increase the amount of
subsidized fertilizer supplied by the FGN or simply add an extra subsidy. 15 There are allegations that in many instances, the product never reaches the warehouses since about 70 percent
is sold in transit in the black market to the retail network (IFDC/PROMIDIA, 2008).. Consequently, about 30
percent of the FGN-subsidized fertilizer reaches the intended farmers. The rest of the product sold in transit
enters the open market as ‘recycled product’ and is sold at a non-subsidized price, normally approaching the
actual market price
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among others, of ensuring food security for the population by developing local production. The
Nigerian “New Agricultural Policy Thrust,” issued in 2001, assigned the agricultural sector an
important role in its strategic planning frameworks. This policy is supported by a number of sub-
sector policies, such as the National Fertilizer Policy for Nigeria and the National Policy on
Integrated Rural Development, both of which are crucial for the attainment of national food security16.
The National Fertilizer Policy for Nigeria, adopted in 2006, is comprehensive and has the
broad aim of “facilitating farmers’ timely access to adequate quantity and quality of fertilizers at
competitive and affordable prices.” The policy launched many desirable principles including market
friendliness, truth-in-labeling and environmental integrity, among others. In addition, it indicated
directions for government intervention in the following domains: fertilizer production, international
trade, domestic marketing, research and development, quality control, environmental impacts, farm
use and governance and institutions. As such, this policy provides broad guidance on government
actions to develop the fertilizer sub-sector in harmony and in support of the organised agricultural
development. The challenge has been to translate these policies and guidelines into a politically
coherent and feasible implementation strategy. The implementation of some of the principles in the
policy document has been neglected, specifically those dealing with regulatory mechanisms (The New
Nigerian Agricultural Policy, 2009). Other than quality assurance, some of the major constraints
facing the fertilizer sub-sector are identified in the policy document as:
• Increase and improve the use of fertilizers.
• Achieve agricultural competitiveness through fertilizer usage.
• Induce and sustain nutrient use efficiency.
• Safeguard the environment with fertilizer production and use.
• Exploit available raw materials for fertilizer production.
• Raise employment in the fertilizer industry
Since 1970s, Nigeria government has been subsidizing fertilizer procurement in Nigeria.
Fertilizer subsidy has been central to the agricultural policy direction of Nigeria and has been justified
on many grounds such as market failures and equity considerations and as a mechanism for dealing
with skewed income distribution(Crawford et al, 2005). Since the late 1970’s, fertilizer has typically
been subsidized, with rates that has been as high as 80 percent. The federal government under the
Federal Market Stabilization Programme (FMSP) procures fertilizer for sale to states at a subsidy of
25 percent and in addition to this, extra subsidy is also provided by the states and local government
councils (IDEP, 2011).
16 Full details of other agricultural policies and how they are aligned with the current Agricultural
Transformation Agenda of the present government are outlined in Appendix 3.
11
However, the review of Nigerian fertilizer subsidy indicates an inconsistency of government
fertilizer policy over the years (Nagy and Edun (2002); Ogunfowora and Odubola (1994);
Ogunfowora (2000) and Kwa (2002). Policies kept changing almost year by year to try to answer
problems of availability, leakage and arbitrage. The Federal Government of Nigeria (FGN) monopoly
on pre-1996 fertilizer procurement and the subsidy policy stymied the private sector. The FGN did not
properly follow through on the liberalization process started in 1997 by ensuring that the
preconditions for a transition to a privatized fertilizer sector were implemented. The FGN opted for a
full withdrawal from fertilizer procurement and subsidy, leaving the industry stranded. The private
sector did respond, but the ad hoc procurement/ subsidy policies of the FGN in 1999, 2001 and 2002
were damaging to the growth of the private sector. Annual fertilizer use fell by about 50% in the post-
1996 as compared with the pre-1996 period. The main constraints to fertilizer use were high prices,
low fertilizer quality and non-availability of fertilizer at the time required (IDEP, 2011). Government
fertilizer policies also had an effect on national, state, and local government budgets. Between 1975
and 2007, the fertilizer subsidy cost as a percentage of the national agricultural budget ranged from
0% to as high as 80% (FAO, 2012). Government fertilizer policy also failed to capture the benefits of
using the considerable resources available in Nigeria to produce fertilizer for in-country use and for
export to the rest of Africa.
Until recently, the Federal Market Stabilization Program (FMSP) remained an integral part of
fertilizer policy in Nigeria and accounted for 43 percent of total capital spending in agriculture from
2001 through 2005 (Mogues et al. 2008). In May 2006, the Federal Executive Council approved the
National Fertilizer Policy with the objective to facilitate farmers' timely access to adequate quantity
and quality of both organic and inorganic fertilizers at competitive but affordable prices in the
country. Based on experiences from other countries such as Malawi and Mozambique, the
International Fertilizer Development Centre (lFDC) in collaboration with the Federal Ministry of
Agriculture and Rural Development, piloted a Fertilizer Voucher Program (FVP) in Kano and Bauchi
States in 2008. The programme was expanded incrementally in 2009 and 2010. It demonstrated the
feasibility and efficiency of a voucher system to administer subsidies to farmers which indicated that
smallholder farmers could benefit directly from the private sector supply of subsidized fertilizers.
Arising from above, in March, 2011, the Fertilizer Voucher Programme (as a Policy Instrument) was
adopted nationwide. The Ministry has therefore designed the Growth Enhancement Scheme (GES) for
implementation in all the States and FCT. The rationale for the Growth Enhancement Support Scheme
(GES)17 is premised on building on the successes achieved through the Voucher Scheme to target
beneficiaries through the electronic system(E-wallet), by encouraging the delivery of GES, via the
development of private sector distribution channels.
17 Federal Ministry of Agriculture and Rural Development (2012). Growth Enhancement Scheme. Available on
the internet at http://www.fmard.gov.ng/index.php/ges/86-ges-overview
12
2.3 Review of Effectiveness of Fertilizer Subsidy Policies
The main reason for advocating fertilizer subsidies is that farmers are very poor and typically
lack sufficient cash resources to buy productive inputs, which can result in suboptimal input use.
Indeed, poverty combined with financial constraints may generate high discount rates that can lead to
low investment (Holden, et al, 1998). In 2005, Malawi was the first country to reintroduce high levels
of input subsidies to improve national food self-sufficiency and reduce its dependence on food aid. In
a short time, Malawi managed to turn a food deficit into a food surplus, and was considered to be a
success story (Denning et al, 2009). The new twist to this subsidy program was that it was targeted
poor smallholders through a coupon system. Other countries have copied Malawi, and similar
programs have arisen and expanded in Ghana, Kenya, Tanzania and Zambia (Dorward and Chirwa,
2011; Minde et al, 2008).
Chirwa et al (2011) revealed that the main goal of the Farm Input Subsidy Programme (FISP)
in Malawi is to raise incomes and household food security of up to 2 million (out of 3.4 million)
smallholder farmers through improvements in their agricultural productivity. The programme
targets smallholder farmers who have land but cannot afford to purchase inputs (principally maize
seed and fertilisers) at market prices. However, Holden and Lunduka (2013b) working on experiment
on input subsidies, cash constraints and timing of supply suggest that low use of agricultural inputs
in Malawi is primarily caused by limited ability to buy inputs and not time-inconsistent behavior.
They recommended that the current input subsidy design in Malawi should be replaced by smarter and
more cost-effective designs that involve smaller packages of fertilizer and delivery of inputs at harvest
time, as well as at planting time. Dorward and Chirwa (2011) in their study on agricultural input
subsidy programme in Malawi showed that the use of voucher as smart subsidy had similar
shortcomings just like the universal subsidy programme. Similar findings were also observed by
Holden and Lunduka (2013a) in Malawi where a subsidy program aimed to provide coupons for
purchase of subsidized fertilizer and seeds targeted at poor rural households also faced serious
problem. The critical findings were that the poverty and vulnerability reduction potentials of the
programme were not optimal, leakages of coupons and fertilizers and misallocation of coupons away
from the needy resulted through rent seeking.
Chirwa et al (2011) working on conceptualizing graduation from agricultural inputs subsidies
in Malawi, considered ways in which the concept of graduation may be usefully applied to the Farm
Input Subsidy Programme (FISP) and sets out a broad conceptualisation of graduation for potential
application in programme design and implementation. For the Malawian farmers to graduate from
relying on fertilizer subsidy and be able to purchase fertilizer at competitive price, they recommended
potential graduation conditions which include reduced input prices, substitution with cheaper inputs,
increased working capital for input purchases, diversification out of maize production, and access to
low cost credit for input purchases.
13
Duflo et al (2008) tested the hypothesis in Kenya of the possibility that, while fertilizer and
hybrid seed increase yield on model farms, they are actually not profitable on many small farms,
where conditions are less than optimal. They revealed that the mean estimates of yield increases due
to fertilizer use are in the range of the estimates found on model farms. They found that the mean rate
of return to using the most profitable quantity of fertilizer they examined was 36% over a season, or
69.5% on an annualized basis. However, other levels of fertilizer use, including the combination of
fertilizer plus hybrid seed recommended by the Kenya Ministry of Agriculture, are not profitable
for farmers in their sample. Thus, while fertilizer can be very profitable when used correctly, one
reason why farmers may not use fertilizer and hybrid seeds is that the official recommendations are
not adapted to many farmers in Kenya. This also suggests that fertilizer is not necessarily easy to use
correctly, which implies that it may not be profitable for many farmers who do not use the right
quantity.
Duflo, et al (2011) conducted a study and social experiments in Kenya and found that poor
households are willing to invest in response to small, time-limited discounts in the form of free
fertilizer delivery just after harvest. Indeed, a 50% subsidy on fertilizer at planting time did not
increase fertilizer use more than this harvest-time free delivery discount. These authors’ finding may
indicate that the distribution and sales of fertilizer just after harvest can be a more effective system
than the sale of fertilizers at planting time, when households may no longer have sufficient funds
remaining from the sale of the previous year’s harvest. The purchase of inputs at harvest time for the
next growing season may serve as a commitment device (DellaVigna, 2009) and reduce the need
for subsidies.
Banful (2010) evaluated the Ghana’s 2008 fertilizer subsidy programme. He observed the role
that political influence can play in a fertilizer subsidy even in programmes that incorporate the new
best practices of fertilizer subsidies ( e.g voucher system). He noticed the evidence of “vote-buying”
activity in Ghana’s 2008 subsidy program which suggests that despite the innovations in design and
implementation of fertilizer subsidies, the new programs have the potential to experience at least some
of the significant pitfalls of former subsidy programs. The current innovations are not enough to make
the new fertilizer subsidy programs economically and socially efficient. He indicated that the farmers
collected vouchers that they had no intention of using or could not afford to use. They rightly
predicted that there would be periods of shortage of vouchers and sold the vouchers to other farmers
who desperately needed to apply fertilizer.
Banful et al (2010) opined that the parallel sales of subsidized and market fertilizer
(unsubsidized) in Nigeria tend to create an avenue for lower-priced subsidized fertilizers to be
diverted for sale at higher market prices. These shortcomings of fertilizer subsidies led to introduction
of vouchers or smart subsidies or coupons. The vouchers imply farmers are given vouchers and make
purchases from private input suppliers. The cost of the fertilizer to the farmer is reduced by the value
14
of the voucher. The supplier in turn is reimbursed for its value at designated banks. A number of
advantages were attributed to the use of vouchers which are: reducing the costs like transportation and
storage by the government, building the private-sector distribution network, serves as a sure
opportunity to secure the input by a farmer holding a voucher and a replacement for food aid in case
of need among others (Minot and Benson, 2009).
Recently, Kabir (2014) conducted a study on political economy of fertilizer subsidy in
Nigeria. He indicated that the trend of leadership in the country has led to inconsistencies and
instability in fertilizer subsidy polices in Nigeria. He also concluded that the gains are not widely
spread among the targeted beneficiaries hence, a negative implication on the increased food
production programme. He showed further in his study that majority of the famers disagreed that the
fertilizer subsidy was timely available (65.3%). He recommended that Nigerian Government
involvement in procurement and distribution of fertilizer should be redefined.
All these shortcoming associated with fertilizer subsidy led the Nigeria to adopt GES, where
private sectors played the role of supplying and distribution of fertilizer and government involved the
registration and payment of 50% of the fertilizer and other agro inputs received by the farmers. The
hope is that this would better serve the intended beneficiaries who are farmers and reduce the fiscal
burden of universal fertilizer subsidy from the government and makes it more effective. However,
there is need to find if this new scheme is better than the previous ones that have been implemented
and test its pro-poor objectives in Nigeria.
2.4 Conceptual Framework for Benefit Incidence Analysis
Benefit incidence analysis (BIA) is better understood in relation to the concepts of targeting
and progressivity of social spending. Targeting is a tool used to select eligible beneficiaries of any
government intervention. In principle, it should concentrate the benefits of social assistance
programmes to the poorest segments of the population. All targeting mechanisms share a common
objective: to correctly identify which households or individuals are poor and which are not. Targeting
is a means of increasing the efficiency of the program by increasing the benefits that the poor can get
with a fixed programme budget (Coady et al, 2004). Conversely, it is a means that will allow the
government to reduce the budget requirement of the program while still delivering the same level of
benefits to the poor. One way to assess the targeting of government subsidies is with reference to the
graphical representation of the distribution of benefits, i.e., concentration curve or benefit
concentration curve. A concentration curve is generated by plotting the cumulative distribution
of “benefits” of public spending on the y-axis against the cumulative distribution of population sorted
by per capita income/consumption/asset on the x-axis. One can assess the progressivity or regressivity
of a public subsidy by comparing the benefit concentration curve with the 45-degree diagonal and the
Lorenz curve of income/ consumption/asset. The diagonal indicates neutrality in the distribution of
benefits. If the distribution of benefits lies along this line, the poorest 20 percent of the population gets
15
20 percent of the subsidy. Thus, the diagonal reflects perfect equality in the distribution of benefits
and it is also referred to as perfect equality (PE) line. The distribution of benefits is said to be
progressive(pro-poor) if the lower income groups receive a larger share of the benefits from
government subsidy than the richer income groups. For instance, if the concentration curve lies above
the diagonal, then the poorest 20% of the population receives more than 20% of the benefits and the
distribution of benefits is said to be progressive in absolute terms or pro-poor (Figure 1). Conversely,
if the benefit concentration curve lies below the diagonal, then the poorest 20% of the population
captures less than 20% of the benefits and the distribution of benefits is said to be regressive in
absolute terms.
Figure 1: Lorenz and Concentration Curves of Benefit
Source: Cuenca(2008)
On the other hand, a benefit concentration curve that lies above the Lorenz curve of
income signifies progressivity of public subsidy relative to income. To wit, the benefits share of
the poorest 20% of the population is larger than its income share. Thus, if the benefits from
the government service are converted to its income equivalent, the post-subsidy distribution
of income-cum-benefit would be more equitable than the original distribution of income if the benefit
concentration curve lies above the Lorenz curve of income. Conversely, a concentration curve that
lies below the Lorenz curve of income distribution suggests transfers that are more regressively
distributed than income. The concentration coefficient (index), also called Suits index, is the most
common summary measure of benefit incidence. It is estimated in like manner as Gini coefficient but
it is based on concentration curve instead of the Lorenz curve (Cuenca, 2008). While Gini coefficient
is computed as the ratio of the area between the diagonal and the Lorenz curve to the total area below
the diagonal, the concentration coefficient is the ratio of the area bounded by the diagonal and the
concentration curve to the total area below the diagonal.
16
If the distribution of benefits is pro-poor, the Suits index is negative. Conversely, if the
distribution of benefits is regressive in absolute terms, then the Suits index is positive. On the other
hand, if the Suits index is algebraically smaller than the Gini coefficient, then the distribution of
benefits is said to be progressive relative to the distribution of income.
3.0 The Methodology
3.1 Data Sources and Collection
This study was carried out in Nigeria. Nigeria lies between 40161 and 130531 North Latitude
and between 20401 and 140411 East Longitude. It is located in the West Africa bordered on the West
by the Republic of Benin, on the north by the Republic of Niger and on the east by the Republic of
Cameroon. To the South, Nigeria is bordered by approximately 800 kilometers of the Atlantic Ocean,
stretching from Badagry in the west to the Rio del Rey in the east. The country also occupies a land
area of 923,768 km2 and the vegetation ranges from mangrove forest on the coast to desert in the far
north. Administration-wise, Nigeria consists of 36 states and a Federal Capital Territory. Each state is
further divided into Local Government Areas (LGAs). There are presently 774 LGAs in the country.
The total population of Nigeria stood at 166.2 million in 2012 according to the estimate from Nigeria
Bureau of Statistics (NBS)18.
The study made use of the Nigeria General Household Survey (GHS)-Panel Datasets of
2010/2011 and 2012/2013. These datasets were supplemented with Living Standard Household
Survey for 2004/200519 and secondary data on expenditure on fertilizer subsidy in Nigeria in 2010
and 2012. Data on expenditure on fertilizer subsidy were obtained from Federal Ministry of
Agriculture and Rural Development in Abuja, Nigeria.
The Nigeria General Household Survey (GHS)-Panel was carried out by the National Bureau
of Statistics (NBS)20. The survey was the result of a partnership that NBS has established with the
Federal Ministry of Agriculture and Rural Development (FMARD), the National Food Reserve
Agency (NFRA), the Bill and Melinda Gates Foundation (BMGF) and the World Bank (WB). They
18 Nigeria Population., available on the internet at http://www.tradingeconomics.com/nigeria/population 19 The Living Standard Household Survey had a national coverage, that is, all the 36 states of the Federation
including the Federal Capital Territory of Abuja were covered. The sample design for the survey was a two
stage stratified sample design. The first stage was the division of each state into clusters called Enumeration
Areas (EA), while the second stage was the division of enumeration areas into housing units. One hundred and
twenty (120) EAs were created for each state and 60 EAs for the Federal Capital Territory for the twelve months
survey duration. Ten EAs for each state and five EAs for the FCT were covered per month (The survey was
conducted through the twelve months period. On the whole, 600 households were studied per state and 300 for
the FCT, which make the total sample for the survey to be about 21900 households. Data that were related to
farmers were extracted which constitutes about 7218 farming households. 20 The Nigeria (GHS)-Panel) was supported by the Living Standards Measurement Study - Integrated Surveys
on Agriculture (LSMS-ISA) project undertaken by the Development Research Group at the World Bank. The
LSMS-ISA project aims to support governments in seven Sub-Saharan African countries to generate nationally
representative, household panel data with a strong focus on agriculture and rural development. The surveys
under the LSMS-ISA project are modeled on the multi-topic integrated household survey design of the
LSMS; Household, Agriculture, and Community questionnaires are an integral part of every survey effort.
17
developed a method to collect agricultural and household data in such a way as to allow the study of
agriculture’s role in household welfare over time. This GHS-Panel Survey responds to the needs of
the country, given the dependence of a high percentage of households on agricultural activities in the
country, for information on household agricultural activities along with other household information
such as human capital, other economic activities, and access to services and resources. Under the
work of the partnership, a full revision of the questionnaire was undertaken and, at the same time, a
sub-sample of the GHS now forms a panel survey. The panel component applies to 5,000 households
with information on multiple agricultural activities and household consumption. As the focus of this
panel component was to improve data from the agricultural sector and link this to other facets of
household behavior and characteristics, the GHS-Panel drew heavily on the Harmonized National
Living Standards Survey (HNLSS-a multi-topic household survey) and the National Agricultural
Sample Survey (NASS-the key agricultural survey) to create a new survey instrument to shed light on
the role of agriculture in households’ economic wellbeing that can be monitored over time. The first
wave of the GHS-Panel was carried out in two visits to the panel households (post-planting visit in
August-October 2010 and post-harvest visit in February-April 2011). The second wave of the GHS-
Panel was carried out also in two visits to the panel households (post-planting visit in September-
November 2012 and post-harvest visit in February-April 2013). The panel data set are downloadable
at the Living Standards Measurement Study - Integrated Surveys on Agriculture (LSMS-ISA) website
address21.
The sample design was a two-stage probability sampling. The primary sampling Unit (psu)
were the Enumeration Areas (EA). These were selected based on probability proportional to size (Pps)
of the total EAs in each state and FCT and the total household listed in those EAs. A total of 500 EAs
were selected using this method. Households were selected randomly using the systematic selection of
ten (10) households per EA. This involved obtaining the total number of households listed in a
particular EA, and then calculating a sampling interval (S.I) by dividing the total households by ten
(10). The next step was to generate a random start ‘r’ from the table of random numbers which stands
as the Ist selection. Consecutive selection of households was obtained by adding the sampling interval
to the random start. In all, 500 clusters/EAs and 5,000 households were interviewed. These samples
were proportionally selected in the states such that different states had different sample sizes.
However, the selection covers all the Local Government Areas and all the states in Nigeria, The urban
and rural areas were also included in the sample. The Nigeria GHS-Panel datasets have been recently
used by Oseni et al (2014). The information on post-planting and post-harvest questionnaire are
presented in Appendices 1 and 2.
21 http://econ.worldbank.org/WBSITE/EXTERNAL/EXTDEC/EXTRESEARCH/EXTLSMS/0,,contentMDK:2
2949589~menuPK:4196952~pagePK:64168445~piPK:64168309~theSitePK:3358997~isCURL:Y~isCURL:Y~i
sCURL:Y,00.html
18
The summary statistics of the data are presented in Table 1. The table reveals that most of the
socio-economic characteristic of the respondents in the panel data sets such as proportion of the
gender in the sample, the mean age of the respondents, household size and literacy rate did not change
significantly during the two sampling periods. However, there were large differences in expenditure,
farmland size and accessibility to mobile phone. For instance, the average cultivated farmland
declined from 6109.62m2 per farmer in 2010/2011 to 5100.67m2 in 2012/2013 on the average. Other
details that are relevant to this study are presented in Table 1. Appendices 1 and 2 provide further
details on the information requested in the questionnaire used to collect the data.
19
Table 1: Descriptive Statistics of Panel Datasets of 2010/2011 and 2012/2013
Variable 2010/2011 Code 2012/2013 Code
SOCIO-ECONOMIC CHARACTERISTICS OF THE HOUSEHOLDS
Sex Male=49.97% , Female=50.03% Sect1-plantingwi Male=49.47%,Female=50.53% Sect1-plantingw2
Household Size 5.9 Sect9-plantingw1 5.8 Sect9-plantingw2
Literacy Rate 60% Sect2-plantingw1 63% Sect2-plantingw2
Annual Mean Non Food
Expenditure(Post-Planting Period)
N15905.51 Sect84-plantingw1 N59683 Sect8d-plantingw2
Annual Mean Non Food
Expenditure[Others] (Post-
Planting Period)
N2410.14 Sect85-plantingw1 N4055.97 Sect8e-plantingw2
Annual Mean Non Food
Expenditure (Post-Harvest Period)
N13193.13 Sect11d-harvestw1 N31611.20 Sect11d-harvestw2
Annual Mean Non Food
Expenditure(others) Post-Harvest
Period)
N1951.93 Sect11e-harvestw1 N2002.70 Sect11e-harvestw2
Mean General Annual Household
Income(Post Planting Period)
N239100 Sect10-plantingw1 N307436.83 Sect10-plantingw2
Mean Annual Household Income
(Post-Harvest Period)
N216100 Sect13-harvestw1 N253391.78 Sect13-harvestw2
Sample Size 5000 5000
Source: Computed From Panel Datasets of 2010/2011 and 2012/2013
20
3.2 Analytical Procedures
In this study we estimated pro-poor price indices for GES scheme in Nigeria. Average and
marginal benefit incidence analyses were also conducted to estimate the share of the poor and non-
poor in the scheme and to check the pattern of the change in their shares over time in Nigeria.
3.2.1Benefit Incidence Analysis
Benefit Incidence Analysis (BIA) will be performed using Distributive Analysis Stata
Package (DASP) 2.2 procedure as indicated in Araar and Duclos (2009). This will be done for
fertilizer subsidy based on gender, regions, location (rural or urban) and nationally. Benefit incidence
analysis (BIA) is widely used to infer distributional impacts of public spending. It depends on both the
allocation of public spending and the behavior of households in using the services. It estimates the
distribution of public expenditure with a two-step methodology. The first step is to analyze the net
unit costs of providing any service (fertilizer subsidy). These are usually based on officially reported
public spending on the service (fertilizer subsidy) in question. The second step is to analyze the
pattern of utilization of the service (fertilizer subsidy) (e.g. how many units are utilized by poor
households and how many by rich households).
3.2.2 Progressivity of the Benefits (PB)
Progressivity of Benefit (PB) was also conducted using Distributive Analysis Stata Package
(DASP) 2.2 procedure. In following their procedure we estimated the progressivity of fertilizer
subsidy by comparing its Lorenz and concentration curves. In doing this, the fertilizer subsidy used by
the farmers were ranked according to their associated farm size (asset) expenditure. The fertilizer
subsidy scheme is considered pro-poor if the concentration curve for its benefit lies anywhere above
the line of Perfect Equality. This means that such fertilizer subsidy scheme accrue more to the poor
than non-poor. A non-pro-poor subsidy scheme has its concentration curve of its benefit lying below
the line of Perfect Equality. The graphical analysis will be supplemented with Concentration Index
and Kakwani Index of Progressivity. Normally, the higher the Concentration index, the more
concentrated is the fertilizer subsidy and the higher the inequality. Hence, of the two fertilizer subsidy
schemes, the more regressive one would be associated with the highest concentration index (Kamgnia,
2008).
Kakwani index22 is directly related to the graphical method described above. The Kakwani
index is defined as twice the area between a payments’ concentration curve and the Lorenz curve and
is calculated as:
dpPLPLKorPLPLK xcxc )()(2)()(
1
0
(1)
22 http://siteresources.worldbank.org/INTPAH/Resources/Publications/Quantitative Techniques/health_eq_tn16.
21
Where, K is the Kakwani index of progressivity, Lc(P) is the fertilizer payment concentration index
and Lx(P) is the Gini Coefficient of the prepayment income( expenditure).
The value of K ranges from –2 to 1. A negative number indicates regressivity; a positive number
indicates progressivity. In the case of proportionality, the concentration lies on top of the Lorenz
curve and the index is zero. It should be noted that the Kakwani Index of Progressivity could also be
zero if the Concentration and Lorenz curves were to cross; the negative and positive differences
between them cancel. Given this, it is important to use Kakwani Index of Progressivity, or any
summary measure of progressivity, as a supplement to, and not a replacement of, the more general
graphical analysis (O’Donnelle et al, 2007).
3.2.3 Marginal Benefit Incidence Analysis (Using Panel Surveys)
We also estimated the marginal benefit incidence of fertilizer subsidy using two consecutive
cross-sectional surveys of 2010/2011 and 2012/2013. Following the methodology suggested by van
de Walle (1995, 2002). The change in quintile participation in fertilizer subsidy between the two
years can then be represented by:
(Fj2/F2) - (Fj1/F1) j= 1, 2 (2)
where Fjt is the number of farmers in welfare quintile j, at date t = 2010, 2013 and Ft is the total
number of farmers that used fertilizer at date t. Alternatively, this can be interpreted as the marginal
incidence of spending on fertilizer subsidy between the two years where participation in fertilizer
subsidy uses are multiplied by the appropriate subsidy level. The share of a given quintile in the total
change in fertilizer subsidy can be expressed as:
(Fj2 - Fj1) / (F2 - F1) (3)
3.2.4 Pro-Poor Price Index
Indirect taxes and subsidies have direct impacts on prices. According to Son (2006), to
analyze the effect of subsidies at the margin we can measure the impact of price changes (borne by
the subsidies) on poverty. This can be accomplished by deriving poverty elasticity with respect to
prices of the individual commodities. To derive the elasticity, the demand equations of k commodities
can be represented as q = q (x, P)
Where, p and q are the k x 1 vectors of prices and quantities of k commodities, and x is the disposable
income. We can assume that all individuals face the same price vector, which means that the prices
are fixed across individuals23. Thus, we can write the demand equation as q = q (x), which are the
quantities consumed by an individual with disposable income x24. Utilizing this demand equation, the
disposable income can be written as:
23 The price of fertilizer in Nigeria is the same in every location due to the effect of subsidy or perfect market
condition of ruling price can be assumed. 24 Writing the demand equations in the form of q = q (x) does not imply that all own-price and cross-price
elasticities of demand are zero. It only implies that prices do not vary across individuals
22
k
i
ii xSxqpx1
)()( (4)
Where, pi is the price of the ith commodity and qi(x) is the quantity of the ith commodity consumed by
an individual whose disposable income is x, where i = 1, 2, .... , m. S(x) is the savings of the individual
with income x. Supposing that due to subsidies, the price vector p changes to p*. How will this change
affect the individual's real income? To answer this question, we can consider the cost function e(u, p),
which is the minimum cost required to obtain u level of utility when the price vector is p. The real
income of the individual with income x will change by25
),(*),( puepuex
which, on using Taylor expansion, gives
m
i
iii xqPpx1
)()*(
This equation gives
)(xqp
xi
i
(5)
A general class of a poverty measure that combines three characteristics of poverty is given as
z
o
dxxfxzP , (6)
Differentiating (6) with respect to Pi, and using (5) gives the elasticity of with respect to Pi, as
z
i
i
i
i dxxfxvx
PP
P0
)()(1
(7)
Where vi(x) =piqi(x) is the expenditure on the ith commodity. This elasticity can be written as the sum
of two components:
)(
ii
iii
i
qpqp (8)
where is the mean of the disposable income and ii qp is the mean expenditure of the ith
commodity. The first term in (8) is the income effect of the price increase which is always positive.
The second term is the redistribution or inequality effect of price change. It is the redistribution effect
that tells us whether an increase in price pi hurts the poor proportionally more than the non-poor. If
this component is positive, it means that the increase in the price of ith commodity hurts the poor
proportionally more than the non-poor. This led Son (2006) to propose the pro- poor price index as
25 ),(*),( puepueCV is the compensation variation, the compensation that should be given to an
individual to maintain his or her utility level the same as before the price change.
23
i
ii
s (9)
where
ii
i
qps is the expenditure on the ith commodity as a proportion of the mean of the total
disposable income. If i is greater (less) than 1, an increase in the ith price hurts the poor more (less)
than the non-poor. Thus, if i is greater than 1, then the subsidy on ith commodity is justified, so that
the poor can benefit more relative to the non-poor.
In estimating the pro-poor price index for fertilizer in Nigeria, we estimated poverty elasticity
with respect to changes in price of fertilizer ( i ), the proportion of disposable income of the farmers
spent on fertilizer ( is ) and growth elasticity of poverty[ change in poverty as result of 1% change in
the mean income of the farmers ( ). Therefore, in this study, Pro-Poor Price Index as indicated in
equation (9) was estimated for fertilizer in 2010/2011 (during the fertilizer Voucher era) and in
2012/2013 (during the e-wallet era), to establish if fertilizer subsidy is justified in the two era. The
procedure for estimating poverty elasticity with respect to income growth and prices is well
established in Araar and Duclos ( 2007) and Kakwani (1993). This is also available in DASP Version
2.2 as designed by Araar and Duclos (2009)26. Son and Kakwani (2006) have equally applied this
methodology to determine the impact of the price changes on poverty in Brazil.
4.0 Preliminary Results and Discussion
4.1 Preliminary Review of GES Scheme in Nigeria
Agriculture is predominantly practiced by resource poor farmers in Nigeria. They lack access
to credit and farm input such as fertilisers, seeds and information to enhance their productivity
(Atofarati, 2014). In view of this, the federal government introduced the Growth Enhancement
Support Scheme (GES) which is designed to deliver government subsidized farm inputs directly to
farmers via GSM phones. The GES scheme is powered by E-wallet, an electronic distribution channel
which provides an efficient and transparent system for the purchase and distribution of agricultural
inputs based on a voucher system. The scheme guarantees registered farmers E-wallet vouchers with
which they can redeem fertilisers, seeds and other agricultural inputs from agro-dealers at 50% of the
cost, the other half being borne by the federal government and state government in equal ratios.
According to Atofarati (2014), this initiative, if well implemented, can be used to help solve the
perennial problem of subsidized fertilizers not getting to the farmers. The initiative would also be
instrumental in reducing bureaucracy and the role of middlemen in fertilizer distribution, which has
26 In estimating the poverty elasticity it is important to set the parameter of inequality aversion (α) at α= 1 or
α=2. For α = 1, the poverty elasticity is estimated based on poverty gap ratio. For α = 2, the poverty elasticity
is estimated based on severity of poverty and takes into account all three characteristics of poverty measure.
24
been marred with corruption and inefficiencies in Nigeria. This direct access to government by
farmers will ensure that progress by the farmers is monitored directly by the government and its
relevant agencies.
The new fertilizer subsidy scheme is part of agriculture transformation agenda (ATA) of the
present government in Nigeria. The main different feature of the ATA when compared with past
agricultural policy in Nigeria is the focusing on value chains of crops where Nigeria has comparative
advantage. Growth Enhancement Scheme is one of the drivers of this value chain. Other supporting
schemes in ATA are presented in Appendix 3 as Nigeria Incentive-Based Risk Sharing for
Agricultural Lending (NIRSAL). This is a loan facility that will enable the Central Bank avail about
N450b (Four hundred and fifty billion Naira) to farmers through the commercial banks. The
Development of Staple Crops Processing Zones is to make each staple crop processing zone to be
accessible, thorough and durable road network, adequate power supply, water and telephone services,
etc, thus enabling access to Nigerian farm produce, locally and internationally. As part of ATA and as
opposed to the former marketing boards, the government also launched Development of Private
Sector Driven, Public Sector Enabled Marketing Corporation to stabilize the price of farm produce..
As earlier said, GES targets supporting twenty million farmers, beginning with 5 million
farmers in the year 2012, with fertilizer and other requisite agro inputs, such as improved rice and
maize seeds (FMARD, 2012). The inclusion of improved rice or maize seeds in the subsidy scheme is
one of the advantages the new scheme has over the old fertilizer subsidy scheme that did not include
provision of complimentary inputs as improved seeds and seedling. The combination of improved
seeds with appropriate fertilizer will improve the yield of the farmers.
Table 2 shows that the current number of farmers registered for GES in stood at 9511674 as at
2013. The farmers’ registration served dual purpose of keeping the bio data of the farmers for
economic and agricultural planning purposes. It also served as indication of interest to participate in
GES programme. Out of the total number of farmers that registered in 2012, only 1090673 of them
were served with fertilizer and improved seeds, however, this has on the average increased by 711%
to 4241855 in 2013. The low percentage redemption rate may be due to low phone penetration rate in
2012 which is estimated to be 37% and this has significantly increased to about 60% in 2013 has
shown in Table 2. The phone accessibility is revealed to have increased in Nigeria from about 73% to
81% among farmers in the study area. The accessibility takes into account the fact that you can make
use of your friend/neigbhbour, etc., to make and receive calls as indicated in Table 4. The low
fertilizer and improved seeds redemption may be due to low number and inactivity of the redemption
centres. Appendix 4 shows that the numbers of redemption centres were 1341 in 2013 and that about
94% of them are active. This is an improvement from about 804 redemption centres in 2012 and in
25
which only 76% of them were active in 201227 as indicated in Appendix 4. Federal Ministries of
Agriculture and Rural Development claims that more redemption and registration centres are being
created to make registration and redemption of e-wallet easier for the farmers.
On further assessment of the scheme reveals that initial lull about the scheme has gradually
being replaced with interest and enthusiasm. This may explain the increase in the number of
registered farmers from 4301661 in 2012 to 9511674 in 2013 which about 121% increase within the
period28. The 9511674 farmers registered in 2013 is closer to the target of 10 million farmers targeted
for the period, with a deviation of about 5%. However, not all the farmers who registered were served
as indicated in Table 2, although the service rate has increased by 711% compared with the previous
years.
We indicated in Table 4 that the literacy rate among the farmers increased from 60% to 63%
between 2010 and 2013. This implies that more than 30% of the farmers are not educated and this
may hamper their chance of participating in the scheme. The scheme makes allowance for illiterate
farmers to bring a relative that can assist them in registering (they have to come together). The
relationship can be confirmed by Identification Card (or any form of Identification). The registration
is done in the native language of the farmers to ensure that they understand the process. The finger
print of the farmer is also collected as a form of identification. The identification process is also
followed during the redemption of the e-wallet through the text message.
The service rate at the rural areas is also a major concern. Although the FMARD has no data
on the service rate at the rural and urban areas, they claimed that the registration is being done at the
Ward level instead of Local Government Council. The Ward is closer to the famers than Local
Government Council as one Local Government Council can have up to 10 Wards. This also will
increase the registration and service point and bring it close to the farmers.
The GES through e-wallet is an improvement over voucher scheme because the voucher can
easily be sold to someone else, but the text message directing farmer to collect fertilizer and agro-
input cannot be easily sold as voucher. Nevertheless, the farmer may which to sell his/her fertilizer
after collection but this may not be rampart as the sales of voucher because of limited number of bags
of fertilizer and agro-inputs(2 bags of fertilizer and 1 bag of maize or rice seeds) the farmers are
entitled to get. The bulkiness of the fertilizer and inputs compared to voucher may discourage their
possible reselling. The fact that the fertilizer and inputs received (2 bags of fertilizer and 1 bag of
maize or rice seeds) are only sufficient to cultivate about one hectare of farmland (which is the
average farm land in Nigeria) may also limit their potential for being resold to another farmers.
The major limitation to the GES scheme is the fact that not all the farmers can register. This is
because the scheme is designed for ‘core poor’ farmers that are resource constrained and are not able
27 http://www.fmard.gov.ng/gesreport/2012/2012-Stats.htm 28 Available on the internet at http://www.fmard.gov.ng/gesreport/2012/2012-Stats.htm
26
to purchase fertilizer and agro-inputs at the competitive prices in the market. They are the ones that
may be willing to go through the long process of registration at the registration centre, wait to receive
text message from Cellulant (Service Provider) that will direct the farmers to designated centre for
redemption of fertilizer and agro-inputs. The limitation of the number of the participating farmers will
enable the government to accurately plan her fiscal burden and resources to make the scheme
effective and efficient.
It should be said that opportunity for rent seeking is highly limited compared with fertilizer
voucher or universal fertilizer subsidy schemes. The role of private sectors is also prominent in the
supply and distribution of fertilizer. The scheme is one of the areas in which FGN and other tiers of
government in Nigeria has cooperated well (World Bank, 2014).
Other countries have shown some sufficient interest in the GES scheme in Nigeria with
possibility of adopting in their countries. For example a four (4) man study tour team came to Abuja
from Malawi on Sunday 7th June, 2014, to under-study the implementation of the Growth
Enhancement Support (GES) Scheme with a view to adopting the scheme in their country29. The study
tour team were in the country for one week (7 days) from 8th – 14th June, 2014, and during the tour
period, they interacted with the relevant GES scheme stakeholders such as the Federal Ministry of
Agriculture and Rural Development officials, Electronic technology platform provider (Cellulant
Nigeria Limited), Supply Chain Managers, (IFDC, Jetlink & Ecalpemos) Input Suppliers, Agro-
dealers and the benefitting farmers30. Similar study tour team was in Nigeria last year 2013 from
Tanzania to under study the GES scheme. FMARD (2014) claimed that about fifty-three (53)
countries in Africa have indicated interest to under- study and implement the GES scheme because of
its laudable achievements, impact and transparent mode of implementation.
According to FMARD Scorecard (2014), limited coverage of the rural areas by mobile phone
networks continued to plague the redemption and reconciliation process in E-wallet Fertilizer Scheme.
Although, this problem is being resolved through the pilot of a smart card technology that does not
require network in the rural areas. Other challenges confronting the schemes are: registration of
farmers started late and this created problems on the field because a number of farmers could not find
their name on the farmer registers; reconciliation of claims had problems because documents
submitted from the field has serious quality control problems; redemption center operations were not
optimal due to the quality of staff and pressure of crowds during redemption; quality of backbone
infrastructure were a problem with mobile networks degraded at the start of the season. This affected
the quality of technology service delivery; poorly defined decision making prerogatives between the
29 http://www.fmard.gov.ng/news_inside.php?nid=129 30 The team is drawn from the Malawian Ministry of Agriculture and Food Security and African
Institute of Corporate Citizenship.
27
state director, GES coordinator and supply chain manager led to an inability to effectively control key
processes like agro-dealer selection on the field.
28
Table 2: Federal Government Information on Growth Enhancement Scheme(GES) ( 2012 to 2013)
Participation Redemption Phone Owners Inputs Received 2012 and 2013
Region Registered
Farmers
Rolled
out
Farmers
No of
Farmers
Served
%
Redeemed.
Versus
Registered
% of
Farmers
(2013)
% of
Farmers
(2012)
NPK
(Unit of
50kg)
UREA
(Unit of
50kg)
Maize
(Unit of
10kg)
Rice
(Unit of
12.5kg)
No of
Farmers
Served
In 2012
No of
Farmers
Served
In 2013
%
Increase
North Central 1700585 1397696 1134506 67 58 39 1228851 1040161 374240 502248 218037 965971 429%
North East 2191351 1902688 1436135 66 63 27 1467291 1404980 333730 402375 366212 1008944 317%
North West 2412625 1574821 1664613 69 42 25 1693009 1636217 356116 874526 371773 1303856 318%
South - East 936029 775675 325494 42 71 48 353812 297077 134439 143440 34969 326107 924%
South-South 1188617 818210 474144 58 59 34 602201 346088 121528 432519 64464 426261 1685%
South-West 1082467 767184 208316 27 64 49 224434 198174 149915 34283 35218 210716 591%
National 9511674 7236274 5243210 55 60 37 5569698 4922697 1469968 2389392 1090673 4241855 711%
Source: FMARD (2014)
29
4.2 Preliminary Results and Discussion of Analysis of Accessibility to Agricultural Inputs by the
Farmers in Nigeria
Until 2006, Nigeria implemented universal fertilizer subsidy scheme. In May 2006, the
Federal Ministry of Agriculture and Rural Development, piloted a Fertilizer Voucher Program (FVP)
in Kano and Bauchi States in 2008. The programme was expanded incrementally to other states in
2009 and 2010. As from March, 2011, the Federal Ministry of Agriculture and Rural Development
designed and implemented the Growth Enhancement Scheme (GES) for implementation in all the
States and FCT. GES premised on building on the Fertilizer Voucher Scheme to target beneficiaries
through the electronic system(E-wallet). The three regimes in which the data were available are
Universal Non-Voucher Fertilizer Regime (2004/2005), Voucher Fertilizer Regime (2010/2011) and
E-wallet Fertilizer Regime (2012/2013).
Table 3 presents the proportion of the farmers that used fertilizer and other inputs during
different fertilizer policy regimes. The table indicates that the proportion of farmers that applied
fertilizer in Nigeria is low. It ranged from about 16% in 2004/2005 to 38% in 20012/2013
respectively. This position has been previously alluded to by Olayide et al (2010). Liverpool-Tasie et
al (2010) indicated that fertilizer use in Nigeria is lower than that observed in other parts of the
developing world, despite the fact that the country is experiencing deteriorating annual nutrient
depletion. Fertilizer subsidy schemes were introduced to correct low fertilizer usage especially among
smallholder farmers by making fertilizer price affordable by them, however, the information on Table
3 suggests that the proportion of farmers that used subsidized fertilizer is even lower. The table shows
that the proportion of the farmers that used subsidized fertilizer increased from about 5% in
2004/2005 to 21% in 2010/2011 and then declined to about 16% in 2012/2013. This finding may cast
doubt on the ability of GES ( E-wallet) to significantly increase fertilizer application among farmers
in Nigeria. It is interesting to know that the average amount of fertilizer used in 2010/2011(46kg) was
lower than the average amount of fertilizer purchased. This implies that is not all the fertilizer
purchased that was used. This creates impression of fertilizer diversion or resale of fertilizer to well-
to-do farmers that has a larger farm size that may need the fertilizer more than available subsidized
quantities. Banful (2010) has also observed that farmers collected vouchers that they had no intention
of using or could not afford to use. They rightly predicted that there would be periods of shortage of
vouchers and sold the vouchers to other farmers who desperately needed to apply fertilizer.
Another important information in Table 3 is that the low use of fertilizer also affected other
inputs. For example, the proportion of the famers that applied herbicides and pesticides(agro-
chemicals) increased from about 15% and 14% in 2004/2005 to about 27% and 15% in 2012/2013
respectively. The proportion of the farmers that made use of modern equipment such as tractors,
ridgers, harvesters and planters were about 4% and 5% respectively. UNECA (2009) reports that SSA
has 13 tractors/100km2 of arable land compared with seven (7) tractors/100km2 in Nigeria (World
30
Bank, 2011). Such low level of mechanization can compromise productivity. Low productivity of
crops in Nigeria has been predicated on the low use of inputs (FAO, 2008). Without increased use of
modern equipment, improved inputs, agrochemicals, fertilizers, improved seeds and soil, agricultural
productive potential in Nigeria may not be realized (Alabi, 2014).
31
Table 3 : Fertilizer and Other Inputs Used During Different Fertilizer Policy Regimes in Nigeria
Non- fertilizer 2004/2005 2010/2011 2012/2013
Fertilizer Subsidy( Non-Voucher) Fertilizer Subsidy (Voucher) Fertilizer Subsidy (E-wallet)
% of farmers who used Fertilizer 15.90 38.84 37.70
% of Farmers who used Subsidized
Fertilizer
5.25 21.02 16.40
Quantity of Fertilizer Purchased - 112.20kg -
Quantity of Fertilizer Purchased and Used - 45.61kg 143.23
% of farmers who used herbicide 14.90 24.70 27.30
% of Farmer who used pesticide 14.10 13.80 14.70
% of Farmers who used modern
agricultural equipment
- 3.46 4.74
% of Farmers who rented modern
agricultural equipment
- 4.50 2.30
Source: Computed by the Authors
32
High cost of inputs may accounts for low use of productive factor among farmers in Nigeria.
This is evident in Table 4, as it reveals that farmers spent N35349 and N30516 on farm inputs in
2010/2011 and 2012/2013 respectively. Comparing these figures with per capita GDP of N149352
(996USD) and N168349(1052USD) in 2011 and 2013, this translated to 24% and 18% of per capita
GDP respectively in 2010/2011 and 2012/201331. This becomes significant if we realized that Nigeria
is high income inequality country and that most of these farmers are poor and spent about 70% of
their income on food (Kuku-Shittu,et al, 2013). High cost of inputs has been attributed to low inputs
use and productivity among farmers in Nigeria(Liverpool- Tasie, et al 2011).
During the Voucher Fertilizer Subsidy participating farmers were provided with vouchers,
which were redeemable at certified agricultural input dealers within their local government of
residence. The voucher provided a N2,000 discount per bag on two bags of Nitrogen Phosphorous
Potassium (NPK 15:15:15) and one bag of Urea. Farmers were required to pay the difference
between the market price and the N2,000 discount per bag (Liverpool-Tasie, et al, 2010a). In the case
of E- wallet, the scheme guarantees registered farmers E-wallet vouchers with which they can redeem
2 bags of fertilizer and a bag of seeds (which may be rice or maize) from agro-dealers at 50% of the
cost, the other half being borne by the federal government and state government in equal ratios. This
suggests that compared with Voucher Fertilizer Subsidy Scheme, E-Wallet delivers less fertilizer ( 2
bags of fertilizer compared with 3bags of fertilizer during Voucher Fertilizer Subsidy Scheme) but
provides additional inputs such as maize or rice seeds. This may be the reason why the cost of seed
payment borne by the farmers reduced from N2974 in 2010/2011 to N2687 in 2012/2013.
It is of note that fertilizer is not the most expensive cost item in Table 4, even if we account
for 21% and 16% of the farmers that purchased subsidized fertilizer in 2010/2011 and 2012/2013
respectively. For instance, while renting of modern agricultural equipment accounted for about 49%
and 46%, cost of fertilizer of accounted for about 29% and 25% of cost of items in 2010/2011 and
2012/2013 respectively. The fact that fertilizer is not the most expensive cost item call to question the
serious focus Federal government of Nigeria has put only on fertilizer subsidy. This reflected on the
fact that despite low budget allocation and fund release to agriculture, expenditure on fertilizer
subsidy alone was usually over 50% of the agricultural capital budget in Nigeria (NTWG, 2009)32.
The recent available figure indicates that subsidy payment constituted about 43% of agriculture
capital expenditure of Federal Government of Nigeria in between 2008 and 2010 and that 60% of the
total agriculture expenditure was capital expenditure (Olomola et al, 2014; Nwoko et al, 2013).
31 http://data.worldbank.org/country/nigeria 32 http://www.npc.gov.ng/downloads/Agriculture%20&%20Food%20Security%20NTWG%20Report.pdf
33
Table 4: Cost of Fertilizer and other Variable Inputs (Naira) Used During Different Fertilizer Policy Regimes in Nigeria
2010/2011 2012/2013
Cost Fertilizer Subsidy
(Universal Fertilizer)
%Contribution Fertilizer Subsidy (E-wallet) %Contribution
Fertilizer 10084 28.53 7756 25.42
Herbicide 266 0.76 2357 7.72
Pesticide 4821 13.64 3650 11.96
Equipment Rent 17204 48.67 14066 46.09
Seed 2974 8.40 2687 8.81
Total 35349 100 30516 100
Source: Computed by the Authors
34
The capital constraints of the farmers could have been addressed if they have access to credit
market from where they can borrow money to finance their farming activities. The important role of
credit in agricultural enterprise development and sustainability has prompted the Federal Government
of Nigeria (FGN) to establish credit schemes such as the Agricultural Credit Guarantee Scheme
(ACGS) and Agricultural Credit Support Scheme (ACSS) to ensure farmers’ access to agricultural
credit33. However, it is clear from Table 5 that none of the farmers in the sample got loan from
Government sources in Nigeria in 2010/2011 and 2012/2013. In 2004/2005, only about 2% got their
loan from Government sources. The fact that majority of Nigerians have not benefited from
government loan has been alluded to by Akramov (2009). when he stated that accessibility to credit
has not improved substantially in Nigeria. The tables shows that the major source of credit to famers
is through informal sources( about 13% and 18% in 2010/2011 and 2012/2013 respectively, while
only about 2% of the farmers go their credit through formal credit sources during the period under
consideration. Enhancing Financial Innovation and Access (EFInA) (2008) notes that 23 percent of
the adult population in Nigeria has access to formal financial institutions, 24 percent to informal
financial services, while 53 percent are financially excluded. The implication of this is that, while
accessibility to formal and informal credit (23% and 24%) is generally low in Nigeria, is more lower
for famers with accessibility of 2% to formal credit financial services34. The problem with informal
credit is that the volume of the credit can be small, This may explain the fact that the mean loan
received by farmers in 2004/2005 was N23412, which may not be enough to finance the input
expenditure of the famers estimated in Table 4. The N23412 estimated as the average loan size
received by the famers is close to N20, 000 as the maximum available credit under the ACGS without
tangible security.(Badiru, 2013). Oke et al (2007) also found that the average loan size from NGO-
MFIs institutions to farmers in southwest Nigeria was N23, 551.25, while actual loan amounts ranged
from N5, 000 to N90, 000. Many factors have been attributed to low accessibility to formal loans by
farmer in Nigeria. According to Okojie et al (2010), the lack of bank accounts, collateral, and
information regarding the procedure for accessing credits from banks limit access to credit from
formal institutions. Table 5 shows that only about 15% and 16% of the farmers have bank accounts in
2010/2011 and 2012/2013 respectively. The importance of credit to reduce the capital constraints of
Nigerian farmers have been emphasized by various scholars. Badiru (2013) posited that timely credit
provision facilitates the timely acquisition of farm inputs, which help farmers improve their
livelihood. Odoemenem and Obinne (2010) reported that productivity and growth are hindered by
limited access to credit facilities by the farmers.
33 http://www.ifpri.org/sites/default/files/publications/nssppn25.pdf 34 It is estimated that only 2.5 percent of total Commercial Bank loans and advances is directed at agriculture in
Nigeria (CBN 2008).
35
Table 5: Financial Institutions and Accessibility to Credit by Farmers in Nigeria
Institutions 2004/2005 2010/2011 2012/2013
Cooperative Society 10.83 52,15 37.01
Saving Association 8,33 16.67 47.76
Micro-Finance 0.42 18.28 9.85
Bank 4.16 12.90 5.37
Government Agencies 2.29 - -
NGO 1.46 - -
Friend and Relative 54.79 - -
Other Informal Sources 26.04 - -
Average amount of Loan N23412 - -
Accessibility
% of Farmers with Bank Account - 15.52 15.78
% of Farmers that used Informal
Credit Sources
- 13.24 17.95
% of Farmers that used formal
Credit Sources
- 1.52 2.32
% of Farmers that used Insurance
Scheme
- 0.28 1.01
Source: Computed by the Authors
4.3 Preliminary Results and Discussion of Analysis of Pro- Poorness of Fertilizer Subsidy
Scheme in Nigeria
In testing the pro-poorness of Universal Fertilize Subsidy Scheme, we compared the Lorenz
of farmland size with concentration curve of accessibility to Universal Fertilize Subsidy Scheme
2004/2005 and General Fertilizer ( subsidized fertilizer and fertilizer at the market price) in Figure 2.
Figure 2 shows that although the concentration curves of accessibility to Universal Fertilize Subsidy
Scheme and General Fertilizer lie above the Lorenz curve they are not far above the line of perfect
Equality which is the condition that can make them pro-poor. The fact that they lies above Lorenz
suggests that fertilizer subsidy during Universal Fertilize Subsidy Scheme was more evenly
distributed than farmland in Nigeria. Since the concentration curves cut across the Line of Perfect
Equality, the final decision about their pro-poorness can only be taken using the concentration indices
presented in Table 6.
36
Figure 2: Lorenz and Concentration Curves of Participation in Universal Fertilizer Scheme in Nigeria
0.2
.4.6
.81
Cum
mu
lative S
hare
of F
ert
ilizer
0 .2 .4 .6 .8 1
Percentiles (p)
Perfect Equality Line Lorenz
General Fertilizer Subidized Fertilizer
Source: Computed by the Authors
In Figure 3 we compared the Lorenz of farmland size with concentration curve of
accessibility to Voucher Fertilizer Subsidy Scheme and General Fertilizer ( subsidized fertilizer and
fertilizer at the market price) in 2010/2011. This was done to answer the question of pro-poorness of
Voucher Fertilizer Subsidy. Figure 3 shows that the concentration curve of accessibility to fertilizer
subsidy lies above the Line of Perfect Equality and concentration curve of accessibility to general
fertilizer( subsidized fertilizer and fertilizer at the market price) in Nigeria. This suggests that
accessibility to fertilizer through Voucher Fertilizer Subsidy Scheme seems to be pro-poor than
accessibility to general fertilizer ( subsidized fertilizer and fertilizer at the market price). This implies
that removal of Voucher Fertilizer Subsidy Scheme without removing the structural, market, credit
and capital constraint that hinder accessibility to fertilizer may limit the accessibility to fertilizer by
the poor farmers in Nigeria. Zoe and Barreiro-Hurle(2012) have isolated limited access, lack of
physical access to fertilizer, lack of credit facility among the constraints limiting accessibility to
fertilizer in Sub-Sahara Africa. Since Lorenz curve lies below concentrative curve of accessibility to
Voucher Fertilizer Subsidy Scheme suggests that fertilizer subsidy is more evenly distributed than
farmland in Nigeria.
37
Figure 3: Lorenz and Concentration Curves of Participation in Voucher Fertilizer Scheme in Nigeria
0.2
.4.6
.81
Cum
mu
lative S
hare
of F
ert
ilizer
0 .2 .4 .6 .8 1
Percentiles (p)
Perfect Equality Line Lorenz
General Fertilizer Subsidized Fert
Source: Computed by the Authors
We compared the Lorenz Curve of farmland size with concentration curve of accessibility to
E-wallet fertilizer subsidy scheme in 2012/2013 and General Fertilizer ( subsidized fertilizer and
fertilizer at the market price) in Figure 4. Figure 4 shows that although the concentration curves of
accessibility to E-wallet fertilizer subsidy scheme and General Fertilizer lie above the Lorenz curve it
is not far above the line of perfect Equality which is the condition that can make them pro-poor. The
fact that they lie above Lorenz curve suggest that accessibility to fertilizer during E-wallet Subsidy
Scheme is more evenly distributed than farmland in Nigeria. The observation that fertilizer subsidy is
more pro-poor than farmland during Voucher and E-wallet Fertilizer Subsidy Scheme implies that
farm size inequality is very real in Nigeria and should be given some consideration. For example,
2010/2011 dataset reveals that the mean farm size in 2010/2011 was 6156m2 with standard deviation
of 15852m2. However, since the concentration curves cut across the Line of Perfect Equality, the final
decision about their pro-poorness can only be taken using the concentration indices presented in
Table 6.
38
Figure 4: Lorenz and Concentration Curves of Participation in E-wallet Fertilizer Scheme in Nigeria
0.2
.4.6
.81
Cum
mu
lative S
hare
of F
ert
ilizer
0 .2 .4 .6 .8 1
Percentiles (p)
Perfect Equality Line Lorenz
General Fert Subsidized Fert
Source: Computed by the Authors
As it has been previously indicated fertilizer subsidy has been central to the agricultural
policy direction of Nigeria and is anchored on the ground of equity considerations (Crawford et al,
2005) and the Government felt that it can be used as a mechanism for dealing with skewed income
distribution in Nigeria. In Table 6, we examined the benefit incidence of fertilizer(using the rate of
farmer’s participation in the fertilizer scheme) during different fertilizer subsidy policy regimes in
Nigeria to check which of the income group benefited most than the others in fertilizer subsidy in
Nigeria. The table shows that, based on concentration indices, fertilizer subsidy is more pro-poor
during Fertilizer Voucher scheme (-0.1150) than during E-wallet Fertilizer scheme(-0.0304), which is
more pro-poor than Non-Voucher Scheme(0.0099). This confirmed our earlier observations in Tables
2 to 4. Apart from concentration indices, the distribution of fertilizer subsidy across the income
quintiles reveals that, while the poorest and richest income groups shared about 26% and 14% of
fertilizer during Voucher Scheme respectively, the shares of the poorest and richest income groups in
E-wallet fertilizer scheme were 18% and 13% respectively. The poorest and richest income groups
shared 17% and 21% of fertilizer subsidy during Universal Fertilizer scheme. The fact that Universal
Fertilizer scheme was not pro-poor may be the reason for its replacement with Voucher Programme as
a Policy Instrument in Nigeria. The Advantage of Fertilizer Voucher Scheme over the universal
fertilizer subsidy scheme in Malawi has been emphasized by Denning et al (2009). However,
39
Dorward and Chirwa (2011) showed that the use of voucher as smart subsidy had similar
shortcomings just like the universal subsidy programme in Malawi.
In a specific case study of Kano and Taraba states in Nigeria, Liverpool-Tasie, et al ( 2010a)
recorded that participating farmers in Voucher Fertilizer programme significantly increased the
likelihood of receiving fertilizer and increased the quantity of subsidized fertilizer received
compared to non-participants. They also indicated that the farmers participating in Voucher Fertilizer
programme paid significantly lower prices compared to those who purchased directly from the
market. However, they indicated that timeliness of fertilizer availability during the Voucher Fertilizer
programme appears to be beyond farmer control. Banful (2010) revealed that Voucher Fertilizer
programme in Ghana, though very innovative, has the potential to experience at least some of the
significant pitfalls of Universal Fertilizer subsidy programme in Ghana. He concluded that current
innovations(Voucher Fertilizer programme in Ghana) are not enough to make the new fertilizer
subsidy programme(Voucher Fertilizer programme) economically and socially efficient.
40
Table 6: Benefit Incidence of Fertilizer Subsidy (Participation Rate) During Fertilizer Policy Regimes in Nigeria
Non- fertilizer 2004/2005 2010/2011 2012/2013
Fertilizer Subsidy
(Universal Fertilizer)
Fertilizer Subsidy
(Voucher)
Fertilizer Subsidy
(E-wallet)
Gini of Expenditure/ Farmland Size 0.4114 0.6581 0.6004
Concentration Index of Fertilizer Subsidy 0.0099 -0.1150 -0.0304
Quintile Share (%)
Poorest 16.90 26.20 18.30
Poor 19.60 20.80 21.50
Average 24.40 22.20 21.80
Rich 18.10 17.30 25.30
Richest 21.10 13.50 13.00
Total 100.00 100.00 100.00
Source: Computed by the Authors
41
Since accessibility to fertilizer subsidy may not translate to purchase of fertilizer if there are
structural, market, credit and capital constraint that hinder the purchase of the fertilizer(Zoe and
Barreiro-Hurle, 2012). It is in the light of this we examined the pro-poorness of Voucher and E-wallet
Fertilize Subsidy Scheme using quantity of farmers that purchased fertilizer during the regimes. We
compared the Lorenz of farmland size with concentration curve of quantity of fertilizer purchased
during Voucher Fertilize Subsidy Scheme in 2010/2011 in Figure 5. Figure 5 shows that the
concentration curves of quantity of fertilizer purchased during Voucher Fertilize Subsidy Scheme lies
above the Lorenz curve but it is below the line of Perfect Equality, which means that Voucher
Fertilize Subsidy Scheme is not pro-poor if we consider the quantity of fertilizer purchased by the
farmers during the regime. This finding about the pro-poorness of Voucher Fertilize Subsidy Scheme
will be confirmed using its concentration index presented in Table 7.
.Figure 5: Lorenz and Concentration Curves of Using Voucher Fertilizer Scheme in Nigeria
0.2
.4.6
.81
Cum
mu
lative S
hare
of F
ert
ilizer
0 .2 .4 .6 .8 1
Percentiles (p)
Perfect Equality Line Lorenz
Fertilizer Purchase
Source: Computed by the Authors
In the case of E-wallet Fertilizer Subsidy Scheme, we compared the Lorenz of farmland size
with concentration curve of quantity of fertilizer purchased during E-wallet Fertilizer Subsidy
Scheme in 2012/2013 in Figure 6. Figure 6 shows that the concentration curves of quantity of
fertilizer purchased during E-wallet Fertilizer Subsidy Scheme lies above the Lorenz curve but it is
below the line of Perfect Equality, which means that E-wallet Fertilizer Subsidy Scheme also is not
pro-poor if we consider the quantity fertilizer purchased by the farmers during the regime. This
42
finding about the pro-poorness of E-wallet Fertilizer Subsidy Scheme will be confirmed using its
concentration index presented in Table 7.
Figure 6: Lorenz and Concentration Curves of Using E-wallet Fertilizer Scheme in Nigeria
0.2
.4.6
.81
Cum
mu
lative S
hare
of F
ert
ilizer
0 .2 .4 .6 .8 1
Percentiles (p)
Perfect Equality Line Lorenz
Fertilizer Purchase
Source: Computed by the Authors
In Table 7, we went further to compare the pro-poorness of Voucher Fertilizer Subsidy
Scheme (using the quantity of Fertilizer farmers purchased) with the newly introduced system that
administer fertilizer subsidy using E- wallet. Generally, fertilizer subsidy schemes during the two
policy era were not pro-poor but based on concentration indices which confirmed the observations
made from Figures 5 and 6. Table 7 suggests that fertilizer subsidy is slightly more pro-poor during
Fertilizer Voucher scheme (0.1143) than during E-wallet Fertilizer scheme(0.1813), Apart from
concentration indices, the distribution of fertilizer subsidy across the income quintiles reveals that
middle income group(22.40%) and the rich (24.10%) benefited slightly more in E-wallet system than
during the Fertilizer Voucher regime. The share of the middle income group and the rich during
Fertilizer Voucher scheme were (21.80%) and (24.00%) respectively. Middle income earners who
are mostly government workers can include their names as small scale farmers during the registration
exercise during E-wallet Fertilizer Subsidy Scheme.
We also considered the share of the poor and non-poor in government expenditure on
fertilizer subsidy in 2010/2011 and 2012/2013 in Table 7. The table reveals that the share of the
rich(N6090 million) and the richest(N8070million) income group in government expenditure on
fertilizer subsidy were 3 and 4 times higher than the share of the poorest quintile(N1979 million)
43
respectively. The same trend is evident in 2012/2013 as the share of the rich (N6813 million) and the
richest (N8735 million) income group were 3 and 4 times higher than the share of the poorest
quintile(N2262 million) respectively. The implication of this is that the rich and richest farmers are
the immediate beneficiaries of fertilizer subsidy scheme that are designed to assist poor small-scale
farmers.
The major shortcoming of E-wallet over that of Voucher scheme is the use of mobile phone,
which may add to the cost profile of the farmers. Majority of the farmers may not own mobile phones
and if they have may not have electricity to charge them or lack mobile network especially in the rural
areas. In fact, relating purchase of subsidized fertilizer with accessibility to mobile phone in
2012/2013 dataset, revealed that 79% of those that purchased subsidized fertilizer owned mobile
phone. Low accessibility to mobile phone may affect the pro-poorness of E-wallet Fertilizer Scheme
and its effectiveness. FMARD has also underscored the importance of this finding in its recent review
of the scheme and proposed to improve on it. According to FMARD Scorecard (2014), limited
coverage of the rural areas by mobile phone networks continued to plague the redemption and
reconciliation process in E-wallet Fertilizer Scheme. The FMARD claimed that this problem is being
resolved through the pilot of a smart card technology that does not require network in the rural areas.
44
Table 7: Benefit Incidence of Fertilizer Subsidy (Quantity Purchased Fertilizer) Used During Fertilizer Policy Regimes in Nigeria
2010/2011 2012/2013
Fertilizer Subsidy (Voucher) Fertilizer Subsidy
(E-wallet)
Gini of Farmland Size 0.6581 0.6004
Concentration Index of Fertilizer
Subsidy
0.1443 0.1813
Quintile Share (%) Share in Fertilizer Expenditure
(Nm)
Quintile Share (%) Share in Fertilizer
Expenditure (Nm)
Poorest 7.80 1979.31 8.00 2261.59
Poor 14.60 3704.85 14.60 4127.42
Average 21.80 5531.95 22.40 6332.45
Rich 24.00 6090.19 24.10 6813.04
Richest 31.80 8069.51 30.90 8735.39
Total 100.00 25375.81 100.00 28269.89
Source: Computed by the Authors
45
Table 8 reveals that gender bias is not a serious problem in fertilizer subsidy schemes during
different fertilizer subsidy schemes in Nigeria. The share of the women in fertilizer subsidy declined
from about 50% during the Fertilizer Voucher scheme to 48% in E-wallet Fertilizer Scheme. Many of
the researchers on fertilizer subsidy did not isolate gender bias as a major problem in accessing
subsidized fertilizer in Nigeria (Olomola et al, 2014). However, wealth and education were
distinguishing factors associated with participation in fertilizer subsidy. This indicates that the
poorest and least educated farmers might have been excluded either due to cumbersome program
requirements or limited resources(Liverpool-Tasie, et al, 2010a). Table 8 confirms that education
correlates positively with accessibility to fertilizer in the two regimes. The table shows that those that
attended formal schools shared about 70% and 64% of fertilizer subsidy during Fertilizer Voucher
and E-wallet Fertilizer Schemes respectively. Education may be positively correlated with income and
awareness of the farmers on the need to apply fertilizer and these will increase the possibility of the
educated farmers purchasing and applying fertilizer. This is consonance with the findings of
Liverpool-Tasie, et al (2010a) who observed that the participants in the voucher program in Kano
were mainly farmers who had used subsidized fertilizer in the past and were formally educated.
Table 8: Share of Fertilizer Subsidy According to Gender and Literacy Levels During Fertilizer
Policy Regimes in Nigeria
2010/2011 2012/2013
Fertilizer Subsidy (Voucher) Fertilizer Subsidy (E-wallet)
Gender Share (%)
Male 50.49 51.78
Female 49.51 48.22
Literacy Levels (%)
Literate 57.36 53.46
Non-Literate 42.64 46.54
Formal School Attendance (%)
Attended School 70.60 63.72
No School Attendance 29.40 36.28
Source: Computed the Authors
Poverty is pervasive across Nigeria with 61 percent of the population estimated to live on less
than a dollar a day and 69 percent living below the relative poverty line (NBS, 2012c). Poverty is not
equally distributed, with the highest proportion of poor in the North East and North West zones.
Poverty is also higher in rural areas than urban. Therefore, a pro-poor fertilizer scheme should favour
North East, North West zones and rural area that has the highest concentration of the poor in Nigeria.
It is in the light of this we examined the distribution pattern of fertilizer subsidy based on location and
regions in Nigeria in Table 9. The table shows the share of the rural in fertilizer subsidy declined from
46
about 55% to 49% during Fertilizer Voucher and E-wallet Fertilizer Schemes respectively. This
implies that Fertilizer Voucher subsidy scheme benefited rural areas more than E-wallet Fertilizer
subsidy scheme in Nigeria. It has been indicated that rural area may be at disadvantage in
participating in E-wallet Fertilizer subsidy scheme because of poor quality of mobile phone
infrastructure in Nigeria (FMARD Scorecard, 2014).
The regional distribution of fertilizer subsidy during Fertilizer Voucher and E-wallet Fertilizer
Schemes favoured North East and North West zones. The shared of North East and North West zones
in Fertilizer Voucher schemes were 30.60% and 38.10% respectively. The shared of North East and
North West zones increased to 30.90% and 46.90% respectively in E-wallet Fertilizer subsidy
scheme respectively. The FMARD(2014) has also shown that more farmers in North East and North
West zones were served with subsidized fertilizer using E-wallet than any other regions in Nigeria.
This maybe one of the reasons that E-wallet Fertilizer subsidy scheme is being praised in the Northern
part of Nigeria.
Table 9 : Location and Regional Share of Fertilizer Subsidy (Quantity) During Fertilizer Policy
Regimes in Nigeria
2010/2011 2012/2013
Fertilizer Subsidy (Voucher) Fertilizer Subsidy (E-wallet)
Location Share(%)
Rural 54.85 48.62
Urban 45.15 51.38
Regional Share(%)
North Central 21.40 15.70
North East 30.60 30.90
North West 38.10 46.90
South - East 6.30 4.20
South-South 3.60 2.00
South-West 0. 80 0.30
Total 100.00 100.00
Source: Computed the Authors
4.4 Preliminary Results and Discussion of Analysis of Marginal Benefit of Fertilizer Subsidy in
Nigeria
The benefit incidence analysis reported so far will be a useful guide in an efforts to
redistribute current subsidy among the poor and non-poor, but did not indicate what we happen if
there is cut or increase in fertilizer subsidy. We conducted marginal benefit incidence to answer the
question of impact of cut or increase in fertilizer subsidy expenditure on the poor and non-poor in
47
Nigeria. Figure7 reveals that if fertilizer subsidy expenditure increased by 100% ( double) the share
of the poorest(core poor which is the target of E-wallet fertilizer subsidy), will decline by about 8%(-
0.0791) and the share of the rich will increase by 8%(0.0803). It has been indicated that only about
16% of the farmers participated in E-wallet fertilizer scheme. The accessibility (participation) rate in
E-wallet fertilizer scheme were 15%, 18%, 18%, 21% and 11% for the poorest, poor, average, rich
and richest quintile respectively as presented in Table 10. The table indicates that marginal benefit in
E-wallet fertilizer scheme increases with accessibility to E-wallet Fertilizer subsidy. The poorest
income group that has the lowest accessibility rate (15%) to E-wallet has the lowest marginal benefit(-
0.0791), while the rich quintile with highest accessibility rate (21%) has the highest marginal benefit
(0.0803). The finding suggests that the poor’s initial rate of access to fertilizer subsidy may determine
the relative extent to which the poor will be benefit from the expansion of fertilizer subsidy. Alabi and
Admas (2014) has also reported that the poorest group only benefits more than the richest group from
extra spending on public services in Nigeria in which they already have relatively high access or
participation rate. The structural constraints that limit the participation of the poor in fertilizer subsidy
will also hinder their share of the subsidy if there is expansion of fertilizer scheme in Nigeria.
Figure 7: Marginal Benefit Incidence of Fertilizer Subsidy in Nigeria
Source: Computed by the Authors
48
Table10 :Marginal Benefit and Accessibility to E-wallet Fertilizer Subsidy by the Farmers
Quintile Marginal Benefit Accessibility Rate
Poorest -0.0791 15
Poor 0.0072 17
Average -0.0038 18
Rich 0.0803 21
Richest -0.0049 11
Average 16
Source: Computed by the Authors
5.0 Preliminary Conclusion and Recommendations
The study indicates that the proportion of farmers that applied fertilizer in Nigeria is low. It
ranged from about 16% in 2004/2005 to 38% in 20012/2013. The percentage of farmers that used
subsidized fertilizer is even lower. It ranged from about 5% in 2004/2005 to 21% in 2010/2011 and
then declined to about 16% in 2012/2013. We also observed that accessibility to fertilizer in Nigeria
can be worst off in the absence of fertilizer subsidy scheme, if the structural, market, credit and
capital constraints that hinder accessibility to fertilizer are not eliminated in Nigeria. The low usage of
other inputs is also noticed in the study. This was attributed to capital and credit constraints that
Nigerian farmers are confronted with.
The pro-poorness analysis suggests that while Voucher Fertilizer Subsidy Scheme seems to
be more pro-poor than E-wallet Fertilizer Scheme on the basis of accessibility, none of them was pro-
poor when the analysis is done on the basis of quantity of fertilizer purchased. The study observed
that the major shortcoming of E-wallet over that of Voucher scheme is the use of mobile phone,
which may add to the cost profile of the poor farmers. In fact, relating purchase of subsidized fertilizer
with accessibility to mobile phone in 2012/2013 dataset, revealed that 79% of those that purchased
subsidized fertilizer owned mobile phone. Low accessibility to mobile phone may affect the pro-
poorness of E-wallet Fertilizer Scheme and its effectiveness.
On that basis of the share of the poor in Government expenditure on fertilizer subsidy, the
study shows that the share of the rich (N6090 million) and the richest (N8070million) income group
were 3 and 4 times higher than the share of the poorest quintile(N1979 million) respectively in
2010/2011 in Government expenditure on fertilizer subsidy . The same trend was noticed in
2012/2013, as the share of the rich (N6813 million) and the richest (N8735 million) income group
were 3 and 4 times higher than the share of the poorest quintile(N2262 million) respectively. The
implication of this is that the rich and richest farmers are the immediate beneficiaries of fertilizer
subsidy scheme that are designed to assist poor small-scale farmers in Nigeria.
Apart from income profile, the study shows that education was a distinguishing factor
associated with purchasing fertilizer during fertilizer subsidy scheme in Nigeria. This study confirms
49
that education correlates positively with accessibility to fertilizer during Fertilizer Voucher and E-
wallet Fertilizer Schemes. It shows that those that attended formal schools shared about 70% and
64% of fertilizer subsidy during Fertilizer Voucher and E-wallet Fertilizer Schemes respectively.
The marginal benefit analysis reveals that if fertilizer subsidy expenditure increased by 100%
( double) the share of the poorest(core poor which is the target of E-wallet fertilizer subsidy), will
decline by about 8%(-0.0791), while the share of the rich will increase by 8%(0.0803). The study also
indicated that the marginal benefit in E-wallet fertilizer scheme increases with initial accessibility to
E-wallet Fertilizer subsidy. The finding suggests that the poor’s initial rate of access to a fertilizer
may determine the relative extent to which the poor will be benefit from the expansion of the fertilizer
subsidy scheme. The conclusion is that any constraints that limit the accessibility of the poor farmers
to fertilizer subsidy will also hinder their share of the fertilizer subsidy even the government spend
more on fertilizer subsidy scheme in Nigeria.
All these findings may cast doubt on the ability of E-wallet Fertilizer Scheme to significantly
increase fertilizer application among farmers in Nigeria. Based on these findings we recommend that
the Federal Government should phase out fertilizer subsidy gradually. After 2016, which is the final
year of E-wallet, fertilizer subsidy be replaced with virile fertilizer market that will sell fertilizer at
cheaper price. This can be made possible by encouraging local production of organic and inorganic
fertilizer by private fertilizer firms. All the fertilizer importing firms should be mandated to open their
fertilizer manufacturing firms between now and next year. In 1980s Nigeria has produced more than
50% of total domestic fertilizer supply, hence, the country can produce more than 1980s using the
considerable resources available in Nigeria.
Capital constraint is a limiting factor to accessibility to fertilizer in Nigeria. About N25376
Million and N28270 Million spent on fertilizer subsidy in 2010 and 2012 respectively (Appendix 5)
can be converted to farming input soft loan scheme for the farmers as the farmers need fertilizer other
inputs to increase their productivity.
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APPENDIX 1: INFORMATION IN THE QUESTIONNAIRE: POST PLANTING VISIT.
SECTION TOPIC RESPONDENT DESCRIPTION
COVER COVER FIELD STAFF Household identifier variables, enumerator, supervisor and data entry, clerk
identifiers, date and time of interview and data entry, and observation notes by
enumerator regarding the interview.
1 Roster Household head or spouse Roster of individuals living in the household, relationship to the household,
gender, year of birth, age, marital status, spouse identification, parental status and
place of birth.
2 Education Individuals 5 years and above Educational attainment, school characteristics and expenditures for 2009-10
academic year.
3 Labour Individuals 5 years and above Labour market participation during the last seven days, wage work and domestic
activities within the home.
4 Credit and savings Individuals 15 years and above Savings made, loans or credit received, insurance and remittances by the
household during the last six months and conditions of the transaction.
5 Household assets HOUSEHOLD head Ownership of assets and value
6 Non-farm enterprises Owner or manager of enterprise. Enterprise ownership, status, labor, value of stock, sales, and business costs.
7A Meals Away from Home Most Knowledgeable person Naira value of food consumed outside the home during the last seven days.
7B Household food
Expenditure
Person responsible for food purchases Quantity and value of food consumed within the household during the last seven
days.
8 Household Non-food
Expenditures
Person responsible for household purchases Non-food expenditure during the last week/last month/last six months/last 12
months
9 Food Security HOUSEHOLD head or eligible adult Food security status of households in during the past 7 days/12 months.
57
10 Other Income HOUSEHOLD head or eligible adult Other sources of household income since the new year.
Cover Cover To be completed by field staff. HOUSEHOLD
ID must be copy from HOUSEHOLD to
Agriculture Questionnaire
This section contains household location and identification data as well as
administrative data as regards administering and managing the questionnaire.
11a Plot Roster Owner or manager of plot Information on all post owned and/or managed by the Household. This section
includes data on estimated area, GPS measured area and the GPS measured
location of the plot.
11b Land Inventory Owner or manager of plot Data on plot acquisition, tenure and use
11c Input Costs Owner or manager of plot Use and cost of pesticide, herbicide, animal labor and use of machinery
11d Fertilizer acquisition Owner or manager of plot Access to, use and cost of seeds used on the plot
11e Seed acquisition Owner or manager of plot Data on source, quantity and costs of seeds used on the plot
11f Planted field crops Owner or manager of plot Data on crops planted on the plot, amount of crops planted and expected harvest
11g Planted tree crops Owner or manager of plot This section collects details on tree crops
11h Marketing of agricultural
Surplus
Owner or manager of plot Marketing of agricultural Surplus. Quantities Sold, value and information on
purchaser
11i Animal holdings Farmer or caretaker of animals Data on farm animals owned by the household and commercial activity with
these animals
11j Animal Costs Farmer or caretaker of animals Livestock farmer caretaker activities and costs
58
11k Agriculture by-product Farmer or caretaker of animals Trading activity in agricultural by-products
11l Extension Owner or manager of plot Access to and utilization of technical support from various sources (government
and non-government)
12 Network Roster Farmer, owner or manager of plot Roster of places or business where the household sells and purchases agricultural
produce and /or supplies
Source: Computed From Panel Datasets of 2010/2011 and 2012/2013
APPENDIX 2: INFORMATION IN THE QUESTIONNAIRE: POST HARVEST VISIT
Section Topic Respondent Description
Cover Cover To be completed by field Staff. HOUSEHOLD ID
must be copy from HOUSEHOLD to Agriculture
Questionnaire.
This section contains household location and identification data as well as
administrative data as regards administering and managing the
questionnaire
A1 Land and Dry Season
planting
Farmer, owner or manager of plot Follow-up on use of land for in post-planting visit and data on any
subsequent planting or other use of the plot. Also information collected on
new plots (I.e. added since post-planting visit.
A2 Harvest Labor Farmer, owner or manager of plot Data on labor that was used for crop harvesting, both from household and
hired.
A3 Agricultural
production Harvest of
field and tree Crops
Farmer, owner or manager of plot Quantity and value of field crops produced
A4 Agricultural Capital Farmer, owner or manager of plot Ownership and value of agricultural machinery and tools owned by the
household
59
A5 (A and B) Extension services Farmer, owner or manager of plot Access to and utilization of technical support from various sources
(government and non-government)
A6 Animal Holdings Owner or caretaker of animals Data on farm animals owned by the household and commercial activity with
these animals
A7 Animal costs Owner or caretakers of Animals Expenditure on livestock
A8 Other Agricultural
Income
Farmer or caretaker of animals Income from sale of Agricultural products and not capture, previous section
under crops and livestock.
A9 (A and B) Fishing, Capital and
revenue
Owner of fishing operations SectionA9a: Data on fishing activities, includes capture, harvesting and
processing
Section9b: Data on boat usage and the use of hired labor
A10 Network Roster Farmer, owner or manager of plot Roster of places or businesses where the household sells and purchases
agricultural produce and/or supplies
Source: Computed From Panel Datasets of 2010/2011 and 2012/2013
60
Appendix 3: The Nigeria Agricultural Policies and Agriculture Transformation Agenda
Past Agriculture Policy Objectives Agriculture Transformation Agenda (ATA) Focus
The achievement of self-sufficiency in basic food supply and the attainment
of food security
Focusing on agriculture as a business instead of a developmental project
Increased production of agricultural raw materials for industries Utilising the transformation of the agricultural sector to create jobs, create
wealth and ensure food security
Increased production and processing of export crops, using improved
production and processing technologies
Focusing on value chains where Nigeria has comparative advantage
Generating gainful employment Sharp focus on youths and women
Growth Enhancement Scheme (GES)
Rational utilization of agricultural resources, improved protection of
agricultural land resources from drought, desert encroachment, soil erosion
and flood, and the general preservation of the environment for the
sustainability of agricultural production
Nigeria Incentive-Based Risk Sharing for Agricultural Lending
(NIRSAL)
Promotion of the increased application of modern technology to agricultural
production
Development of Staple Crops Processing Zones
Improvement in the quality of life of rural dwellers.
Development of Private Sector Driven, Public Sector Enabled Marketing
Corporation
Sources: FMARD (2012).
61
Appendix 4: Distribution of Growth Enhancement Scheme Redemption Centres in 2012 and 2013
2013 2012
Total
Redemption
Centres
Active
Redemption
Centres
Non Active
Redemption
Centres
% of Active
Redemption
Centres
Total
Redemption
Centres
Active
Redemption
Centres
Non Active
Redemption
Centres
% of Active
Redemption
Centres
North-Central Region
BEN 36 36 0 100 15 23 -8 153
FCT 23 23 0 100 17 6 11 35
KOG 60 59 1 98 38 21 17 55
KWA 32 32 0 1 20 16 4 80
NAS 29 29 0 1 22 13 9 59
NIG 51 51 0 1 32 23 9 72
PLA 60 57 3 95 15 17 -2 113
TOTAL 291 287 4 99 159 121 40 72
North-East Region
ADA 32 16 16 50 - - - -
BAU 68 58 10 85 42 20 22 48
BOR 27 26 1 96 27 14 13 52
GOM 35 34 1 97 19 11 8 58
TAR 65 56 9 96 33 8 25 24
YOB 17 17 0 100 4 10 -6 250
TOTAL 244 207 37 85 125 76 62 61
62
North-West Region
JIG 56 48 8 86 40 27 8 68
KAD 69 54 15 78 20 23 15 115
KAN 41 25 16 61 21 44 16 210
KAS 33 31 2 94 33 14 2 42
KEB 40 32 8 80 4 14 8 350
SOK 65 56 9 86 35 23 9 66
ZAM 18 15 3 83 4 5 3 125
TOTAL 322 261 61 81 157 150 61 96
South-East Region
ABI 47 47 0 100 10 17 0 170
ANA 55 55 0 100 23 21 0 91
EBO 20 20 0 100 20 13 0 65
ENU 33 33 0 100 13 17 0 131
IMO 27 27 0 100 18 19 0 106
TOTAL 182 182 0 100 84 87 0 104
South-South Region
AKW 37 37 0 100 31 17 0 55
BAY 25 25 0 100 8 3 0 38
CRO 48 48 0 100 37 18 0 49
DEL 58 58 0 100 17 25 0 147
EDO 30 30 0 100 14 18 0 129
63
RIV 14 14 0 100 6 6 0 100
TOTAL 212 212 0 100 113 87 0 77
South-West Region
EKI 26 26 0 100 19 16 0 84
LAG 11 11 0 100 19 6 0 32
OGU 35 35 0 100 21 21 0 100
OND 23 23 0 100 10 11 0 110
OSU 32 32 0 100 30 6 0 20
OYO 65 65 0 100 67 33 0 49
TOTAL 192 192 0 100 166 93 0 56
GRAND
TOTAL
1443
1341
102
94
804
614
163
76
Source: Computed from FMARD (2012).
64
Appendix 5: Federal and States Government Fertilizer Subsidy Allocation in 2010 and 2012 in
Nigeria(Million Naira)
Year Total for the Federal Total for all the States Total Fertilizer Subsidy
2010 13310 14065.81 25375.81
2012 15670 12599.89 28269.89
Source: FMARD, 2014